prompt stringlengths 105 757 | reference_code stringlengths 12 387 | code_context stringlengths 1.3k 3.36k | problem_id int64 511 665 | library_problem_id int64 0 154 | library stringclasses 1
value | test_case_cnt int64 1 1 | perturbation_type stringclasses 2
values | perturbation_origin_id int64 0 154 | user_chat_prompt stringlengths 512 1.16k | test_code stringlengths 974 2.48k | solution_function stringlengths 212 1.29k |
|---|---|---|---|---|---|---|---|---|---|---|---|
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
# Make a scatter plot with x and y and set marker size to be 100
# Combine star hatch and vertical line hatch together for the marker
# SOLUTION START
| plt.scatter(x, y, hatch="*|", s=500) | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.scatter... | 612 | 101 | Matplotlib | 1 | Semantic | 98 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
```
Please help me to:
- Make a scatter plot with x and y and set marker size to be 100
- Combine star hatch and vertical line hatch together for the marker
- save the figure using `pl... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.scatter... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
plt.scatter(x, y, hatch="*|", s=500)
plt.savefig('output.png', bbox_inches ='tight')
result = None
return result |
import matplotlib.pyplot as plt
import numpy as np
data = np.random.random((10, 10))
# Set xlim and ylim to be between 0 and 10
# Plot a heatmap of data in the rectangle where right is 5, left is 1, bottom is 1, and top is 4.
# SOLUTION START
| plt.xlim(0, 10)
plt.ylim(0, 10)
plt.imshow(data, extent=[1, 5, 1, 4]) | import matplotlib.pyplot as plt
import numpy as np
from PIL import Image
import matplotlib
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
data = np.random.random((10, 10))
plt.xlim(0, 10)
... | 613 | 102 | Matplotlib | 1 | Origin | 102 | Given this code block:
```
import matplotlib.pyplot as plt
import numpy as np
data = np.random.random((10, 10))
```
Please help me to:
- Set xlim and ylim to be between 0 and 10
- Plot a heatmap of data in the rectangle where right is 5, left is 1, bottom is 1, and top is 4.
- save the figure using `plt.savefig('outp... | import matplotlib.pyplot as plt
import numpy as np
from PIL import Image
import matplotlib
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
data = np.random.random((10, 10))
plt.xlim(0, 10)
... |
def solve(test_input):
import matplotlib.pyplot as plt
import numpy as np
data = np.random.random((10, 10))
plt.xlim(0, 10)
plt.ylim(0, 10)
plt.imshow(data, extent=[1, 5, 1, 4])
plt.savefig('output.png', bbox_inches ='tight')
result = None
return result |
import matplotlib.pyplot as plt
import numpy as np
x = np.linspace(0.1, 2 * np.pi, 41)
y = np.exp(np.sin(x))
# make a stem plot of y over x and set the orientation to be horizontal
# SOLUTION START
| plt.stem(x, y, orientation="horizontal") | import matplotlib.pyplot as plt
import numpy as np
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.linspace(0.1, 2 * np.pi, 41)
y = np.exp(np.sin(x))
plt.stem(... | 614 | 103 | Matplotlib | 1 | Origin | 103 | Given this code block:
```
import matplotlib.pyplot as plt
import numpy as np
x = np.linspace(0.1, 2 * np.pi, 41)
y = np.exp(np.sin(x))
```
Please help me to:
- make a stem plot of y over x and set the orientation to be horizontal
- save the figure using `plt.savefig('output.png', bbox_inches ='tight')`
I need the s... | import matplotlib.pyplot as plt
import numpy as np
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.linspace(0.1, 2 * np.pi, 41)
y = np.exp(np.sin(x))
plt.stem(... |
def solve(test_input):
import matplotlib.pyplot as plt
import numpy as np
x = np.linspace(0.1, 2 * np.pi, 41)
y = np.exp(np.sin(x))
plt.stem(x, y, orientation="horizontal")
plt.savefig('output.png', bbox_inches ='tight')
result = None
return result |
import matplotlib.pyplot as plt
d = {"a": 4, "b": 5, "c": 7}
c = {"a": "red", "c": "green", "b": "blue"}
# Make a bar plot using data in `d`. Use the keys as x axis labels and the values as the bar heights.
# Color each bar in the plot by looking up the color in colors
# SOLUTION START
| colors = []
for k in d:
colors.append(c[k])
plt.bar(range(len(d)), d.values(), color=colors)
plt.xticks(range(len(d)), d.keys()) | import matplotlib.pyplot as plt
from PIL import Image
import numpy as np
import matplotlib
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
d = {"a": 4, "b": 5, "c": 7}
c = {"a": "red", "c": "g... | 615 | 104 | Matplotlib | 1 | Origin | 104 | Given this code block:
```
import matplotlib.pyplot as plt
d = {"a": 4, "b": 5, "c": 7}
c = {"a": "red", "c": "green", "b": "blue"}
```
Please help me to:
- Make a bar plot using data in `d`. Use the keys as x axis labels and the values as the bar heights.
- Color each bar in the plot by looking up the color in color... | import matplotlib.pyplot as plt
from PIL import Image
import numpy as np
import matplotlib
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
d = {"a": 4, "b": 5, "c": 7}
c = {"a": "red", "c": "g... |
def solve(test_input):
import matplotlib.pyplot as plt
d = {"a": 4, "b": 5, "c": 7}
c = {"a": "red", "c": "green", "b": "blue"}
colors = []
for k in d:
colors.append(c[k])
plt.bar(range(len(d)), d.values(), color=colors)
plt.xticks(range(len(d)), d.keys())
plt.savefig('out... |
import matplotlib.pyplot as plt
# Make a solid vertical line at x=3 and label it "cutoff". Show legend of this plot.
# SOLUTION START
| plt.axvline(x=3, label="cutoff")
plt.legend() | import matplotlib.pyplot as plt
from PIL import Image
import numpy as np
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
plt.axvline(x=3, label="cutoff")
plt.legend()
plt.savefig("ans.png"... | 616 | 105 | Matplotlib | 1 | Origin | 105 | Given this code block:
```
import matplotlib.pyplot as plt
```
Please help me to:
- Make a solid vertical line at x=3 and label it "cutoff". Show legend of this plot.
- save the figure using `plt.savefig('output.png', bbox_inches ='tight')`
I need the solution to fit in a function with the following signature:
```
d... | import matplotlib.pyplot as plt
from PIL import Image
import numpy as np
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
plt.axvline(x=3, label="cutoff")
plt.legend()
plt.savefig("ans.png"... |
def solve(test_input):
import matplotlib.pyplot as plt
plt.axvline(x=3, label="cutoff")
plt.legend()
plt.savefig('output.png', bbox_inches ='tight')
result = None
return result |
import matplotlib.pyplot as plt
labels = ["a", "b"]
height = [3, 4]
# Use polar projection for the figure and make a bar plot with labels in `labels` and bar height in `height`
# SOLUTION START
| fig, ax = plt.subplots(subplot_kw={"projection": "polar"})
plt.bar(labels, height) | import matplotlib.pyplot as plt
from PIL import Image
import numpy as np
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
labels = ["a", "b"]
height = [3, 4]
fig, ax = plt.subplots(subplot_... | 617 | 106 | Matplotlib | 1 | Origin | 106 | Given this code block:
```
import matplotlib.pyplot as plt
labels = ["a", "b"]
height = [3, 4]
```
Please help me to:
- Use polar projection for the figure and make a bar plot with labels in `labels` and bar height in `height`
- save the figure using `plt.savefig('output.png', bbox_inches ='tight')`
I need the solut... | import matplotlib.pyplot as plt
from PIL import Image
import numpy as np
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
labels = ["a", "b"]
height = [3, 4]
fig, ax = plt.subplots(subplot_... |
def solve(test_input):
import matplotlib.pyplot as plt
labels = ["a", "b"]
height = [3, 4]
fig, ax = plt.subplots(subplot_kw={"projection": "polar"})
plt.bar(labels, height)
plt.savefig('output.png', bbox_inches ='tight')
result = None
return result |
import matplotlib.pyplot as plt
l = ["a", "b", "c"]
data = [225, 90, 50]
# Make a donut plot of using `data` and use `l` for the pie labels
# Set the wedge width to be 0.4
# SOLUTION START
| plt.pie(data, labels=l, wedgeprops=dict(width=0.4)) | import matplotlib.pyplot as plt
from PIL import Image
import numpy as np
import matplotlib
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
l = ["a", "b", "c"]
data = [225, 90, 50]
plt.pie(... | 618 | 107 | Matplotlib | 1 | Origin | 107 | Given this code block:
```
import matplotlib.pyplot as plt
l = ["a", "b", "c"]
data = [225, 90, 50]
```
Please help me to:
- Make a donut plot of using `data` and use `l` for the pie labels
- Set the wedge width to be 0.4
- save the figure using `plt.savefig('output.png', bbox_inches ='tight')`
I need the solution ... | import matplotlib.pyplot as plt
from PIL import Image
import numpy as np
import matplotlib
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
l = ["a", "b", "c"]
data = [225, 90, 50]
plt.pie(... |
def solve(test_input):
import matplotlib.pyplot as plt
l = ["a", "b", "c"]
data = [225, 90, 50]
plt.pie(data, labels=l, wedgeprops=dict(width=0.4))
plt.savefig('output.png', bbox_inches ='tight')
result = None
return result |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
# Plot y over x and show blue dashed grid lines
# SOLUTION START
| plt.plot(y, x)
plt.grid(color="blue", linestyle="dashed") | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(y,... | 619 | 108 | Matplotlib | 1 | Origin | 108 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
```
Please help me to:
- Plot y over x and show blue dashed grid lines
- save the figure using `plt.savefig('output.png', bbox_inches ='tight')`
I need the solution to fit in a functi... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(y,... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
plt.plot(y, x)
plt.grid(color="blue", linestyle="dashed")
plt.savefig('output.png', bbox_inches ='tight')
result = None
return result |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
# Plot y over x
# Turn minor ticks on and show gray dashed minor grid lines
# Do not show any major grid lines
# SOLUTION START
| plt.plot(y, x)
plt.minorticks_on()
plt.grid(color="gray", linestyle="dashed", which="minor") | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(y,... | 620 | 109 | Matplotlib | 1 | Origin | 109 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
```
Please help me to:
- Plot y over x
- Turn minor ticks on and show gray dashed minor grid lines
- Do not show any major grid lines
- save the figure using `plt.savefig('output.png'... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(y,... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
plt.plot(y, x)
plt.minorticks_on()
plt.grid(color="gray", linestyle="dashed", which="minor")
plt.savefig('output.png', bbox_inches ='tight')
re... |
import matplotlib.pyplot as plt
labels = ["Walking", "Talking", "Sleeping", "Working"]
sizes = [23, 45, 12, 20]
colors = ["red", "blue", "green", "yellow"]
# Make a pie chart with data in `sizes` and use `labels` as the pie labels and `colors` as the pie color.
# Bold the pie labels
# SOLUTION START
| plt.pie(sizes, colors=colors, labels=labels, textprops={"weight": "bold"}) | import matplotlib.pyplot as plt
from PIL import Image
import numpy as np
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
labels = ["Walking", "Talking", "Sleeping", "Working"]
sizes = [23, 45,... | 621 | 110 | Matplotlib | 1 | Origin | 110 | Given this code block:
```
import matplotlib.pyplot as plt
labels = ["Walking", "Talking", "Sleeping", "Working"]
sizes = [23, 45, 12, 20]
colors = ["red", "blue", "green", "yellow"]
```
Please help me to:
- Make a pie chart with data in `sizes` and use `labels` as the pie labels and `colors` as the pie color.
- Bold... | import matplotlib.pyplot as plt
from PIL import Image
import numpy as np
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
labels = ["Walking", "Talking", "Sleeping", "Working"]
sizes = [23, 45,... |
def solve(test_input):
import matplotlib.pyplot as plt
labels = ["Walking", "Talking", "Sleeping", "Working"]
sizes = [23, 45, 12, 20]
colors = ["red", "blue", "green", "yellow"]
plt.pie(sizes, colors=colors, labels=labels, textprops={"weight": "bold"})
plt.savefig('output.png', bbox_inch... |
import matplotlib.pyplot as plt
labels = ["Walking", "Talking", "Sleeping", "Working"]
sizes = [23, 45, 12, 20]
colors = ["red", "blue", "green", "yellow"]
# Make a pie chart with data in `sizes` and use `labels` as the pie labels and `colors` as the pie color.
# Bold the pie labels
# SOLUTION START
| plt.pie(sizes, colors=colors, labels=labels, textprops={"weight": "bold"}) | import matplotlib.pyplot as plt
from PIL import Image
import numpy as np
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
labels = ["Walking", "Talking", "Sleeping", "Working"]
sizes = [23, 45,... | 622 | 111 | Matplotlib | 1 | Origin | 111 | Given this code block:
```
import matplotlib.pyplot as plt
labels = ["Walking", "Talking", "Sleeping", "Working"]
sizes = [23, 45, 12, 20]
colors = ["red", "blue", "green", "yellow"]
```
Please help me to:
- Make a pie chart with data in `sizes` and use `labels` as the pie labels and `colors` as the pie color.
- Bold... | import matplotlib.pyplot as plt
from PIL import Image
import numpy as np
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
labels = ["Walking", "Talking", "Sleeping", "Working"]
sizes = [23, 45,... |
def solve(test_input):
import matplotlib.pyplot as plt
labels = ["Walking", "Talking", "Sleeping", "Working"]
sizes = [23, 45, 12, 20]
colors = ["red", "blue", "green", "yellow"]
plt.pie(sizes, colors=colors, labels=labels, textprops={"weight": "bold"})
plt.savefig('output.png', bbox_inch... |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
# Plot y over x in a line chart but use transparent marker with non-transparent edge
# SOLUTION START
| plt.plot(
x, y, "-o", ms=14, markerfacecolor="None", markeredgecolor="red", markeredgewidth=5
) | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(
... | 623 | 112 | Matplotlib | 1 | Origin | 112 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
```
Please help me to:
- Plot y over x in a line chart but use transparent marker with non-transparent edge
- save the figure using `plt.savefig('output.png', bbox_inches ='tight')`
I... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(
... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
plt.plot(
x, y, "-o", ms=14, markerfacecolor="None", markeredgecolor="red", markeredgewidth=5
)
plt.savefig('output.png', bbox_inches ='tight')... |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df = sns.load_dataset("penguins")[
["bill_length_mm", "bill_depth_mm", "flipper_length_mm", "body_mass_g"]
]
sns.distplot(df["bill_length_mm"], color="blue")
# Plot a vertical line at 55 with green color
# SOLUTION START
| plt.axvline(55, color="green") | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from PIL import Image
import matplotlib
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
df = sns.load_d... | 624 | 113 | Matplotlib | 1 | Origin | 113 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df = sns.load_dataset("penguins")[
["bill_length_mm", "bill_depth_mm", "flipper_length_mm", "body_mass_g"]
]
sns.distplot(df["bill_length_mm"], color="blue")
```
Please help me to:
- Plot a verti... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from PIL import Image
import matplotlib
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
df = sns.load_d... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df = sns.load_dataset("penguins")[
["bill_length_mm", "bill_depth_mm", "flipper_length_mm", "body_mass_g"]
]
sns.distplot(df["bill_length_mm"], color="blue")
... |
import matplotlib.pyplot as plt
import numpy as np
# Specify the values of blue bars (height)
blue_bar = (23, 25, 17)
# Specify the values of orange bars (height)
orange_bar = (19, 18, 14)
# Plot the blue bar and the orange bar side-by-side in the same bar plot.
# Make sure the bars don't overlap with each other.
# ... | # Position of bars on x-axis
ind = np.arange(len(blue_bar))
# Figure size
plt.figure(figsize=(10, 5))
# Width of a bar
width = 0.3
plt.bar(ind, blue_bar, width, label="Blue bar label")
plt.bar(ind + width, orange_bar, width, label="Orange bar label") | import matplotlib.pyplot as plt
import numpy as np
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
blue_bar = (23, 25, 17)
orange_bar = (19, 18, 14)
ind = np.arange(l... | 625 | 114 | Matplotlib | 1 | Origin | 114 | Given this code block:
```
import matplotlib.pyplot as plt
import numpy as np
blue_bar = (23, 25, 17)
orange_bar = (19, 18, 14)
```
Please help me to:
- Specify the values of blue bars (height)
- Specify the values of orange bars (height)
- Plot the blue bar and the orange bar side-by-side in the same bar plot.
- M... | import matplotlib.pyplot as plt
import numpy as np
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
blue_bar = (23, 25, 17)
orange_bar = (19, 18, 14)
ind = np.arange(l... |
def solve(test_input):
import matplotlib.pyplot as plt
import numpy as np
blue_bar = (23, 25, 17)
orange_bar = (19, 18, 14)
# Position of bars on x-axis
ind = np.arange(len(blue_bar))
# Figure size
plt.figure(figsize=(10, 5))
# Width of a bar
width = 0.3
plt.... |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.random.rand(10)
z = np.random.rand(10)
a = np.arange(10)
# Make two subplots
# Plot y over x in the first subplot and plot z over a in the second subplot
# Label each line chart and put them into a single legend on the fir... | fig, ax = plt.subplots(2, 1)
(l1,) = ax[0].plot(x, y, color="red", label="y")
(l2,) = ax[1].plot(a, z, color="blue", label="z")
ax[0].legend([l1, l2], ["z", "y"]) | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.random.rand(10)
z = np... | 626 | 115 | Matplotlib | 1 | Origin | 115 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.random.rand(10)
z = np.random.rand(10)
a = np.arange(10)
```
Please help me to:
- Make two subplots
- Plot y over x in the first subplot and plot z over a in the second subplot
- Label each line... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.random.rand(10)
z = np... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.random.rand(10)
z = np.random.rand(10)
a = np.arange(10)
fig, ax = plt.subplots(2, 1)
(l1,) = ax[0].plot(x, y, color="red", label="y")
(l2,) = ax[1].plot(... |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib
x = np.arange(10)
y = np.linspace(0, 1, 10)
# Plot y over x with a scatter plot
# Use the "Spectral" colormap and color each data point based on the y-value
# SOLUTION START
| plt.scatter(x, y, c=y, cmap="Spectral") | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.linspace... | 627 | 116 | Matplotlib | 1 | Origin | 116 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib
x = np.arange(10)
y = np.linspace(0, 1, 10)
```
Please help me to:
- Plot y over x with a scatter plot
- Use the "Spectral" colormap and color each data point based on the y-value
- save the figure usin... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.linspace... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib
x = np.arange(10)
y = np.linspace(0, 1, 10)
plt.scatter(x, y, c=y, cmap="Spectral")
plt.savefig('output.png', bbox_inches ='tight')
result = None
return res... |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
# plot y over x
# use a tick interval of 1 on the a-axis
# SOLUTION START
| plt.plot(x, y)
plt.xticks(np.arange(min(x), max(x) + 1, 1.0)) | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(x,... | 628 | 117 | Matplotlib | 1 | Origin | 117 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
```
Please help me to:
- plot y over x
- use a tick interval of 1 on the a-axis
- save the figure using `plt.savefig('output.png', bbox_inches ='tight')`
I need the solution to fit i... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(x,... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
plt.plot(x, y)
plt.xticks(np.arange(min(x), max(x) + 1, 1.0))
plt.savefig('output.png', bbox_inches ='tight')
result = None
return result |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df = sns.load_dataset("penguins")[["bill_length_mm", "species", "sex"]]
# Use seaborn catplot to plot multiple barplots of "bill_length_mm" over "sex" and separate into different subplot columns by "species"
# Do not share y ... | sns.catplot(
x="sex", col="species", y="bill_length_mm", data=df, kind="bar", sharey=False
) | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
df = sns.load_dataset("penguins")... | 629 | 118 | Matplotlib | 1 | Origin | 118 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df = sns.load_dataset("penguins")[["bill_length_mm", "species", "sex"]]
```
Please help me to:
- Use seaborn catplot to plot multiple barplots of "bill_length_mm" over "sex" and separate into differe... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
df = sns.load_dataset("penguins")... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df = sns.load_dataset("penguins")[["bill_length_mm", "species", "sex"]]
sns.catplot(
x="sex", col="species", y="bill_length_mm", data=df, kind="bar", sharey=False
... |
import matplotlib.pyplot as plt
# draw a circle centered at (0.5, 0.5) with radius 0.2
# SOLUTION START
| import matplotlib.pyplot as plt
circle1 = plt.Circle((0.5, 0.5), 0.2)
plt.gca().add_patch(circle1) | import matplotlib.pyplot as plt
from PIL import Image
import numpy as np
import matplotlib
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
circle1 = plt.Circle((0.5, 0.5), 0.2)
plt.gca().add_p... | 630 | 119 | Matplotlib | 1 | Origin | 119 | Given this code block:
```
import matplotlib.pyplot as plt
```
Please help me to:
- draw a circle centered at (0.5, 0.5) with radius 0.2
- save the figure using `plt.savefig('output.png', bbox_inches ='tight')`
I need the solution to fit in a function with the following signature:
```
def solve(input):
# Receive... | import matplotlib.pyplot as plt
from PIL import Image
import numpy as np
import matplotlib
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
circle1 = plt.Circle((0.5, 0.5), 0.2)
plt.gca().add_p... |
def solve(test_input):
import matplotlib.pyplot as plt
import matplotlib.pyplot as plt
circle1 = plt.Circle((0.5, 0.5), 0.2)
plt.gca().add_patch(circle1)
plt.savefig('output.png', bbox_inches ='tight')
result = None
return result |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
# Plot y over x and use the greek letter phi for title. Bold the title and make sure phi is bold.
# SOLUTION START
| plt.plot(y, x)
plt.title(r"$\mathbf{\phi}$") | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(y,... | 631 | 120 | Matplotlib | 1 | Origin | 120 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
```
Please help me to:
- Plot y over x and use the greek letter phi for title. Bold the title and make sure phi is bold.
- save the figure using `plt.savefig('output.png', bbox_inches =... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(y,... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
plt.plot(y, x)
plt.title(r"$\mathbf{\phi}$")
plt.savefig('output.png', bbox_inches ='tight')
result = None
return result |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
# Plot y over x with a legend of "Line"
# Adjust the spacing between legend markers and labels to be 0.1
# SOLUTION START
| plt.plot(x, y, label="Line")
plt.legend(handletextpad=0.1) | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(x,... | 632 | 121 | Matplotlib | 1 | Origin | 121 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
```
Please help me to:
- Plot y over x with a legend of "Line"
- Adjust the spacing between legend markers and labels to be 0.1
- save the figure using `plt.savefig('output.png', bbox_... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(x,... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
plt.plot(x, y, label="Line")
plt.legend(handletextpad=0.1)
plt.savefig('output.png', bbox_inches ='tight')
result = None
return result |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
# Plot y over x with a legend of "Line"
# Adjust the length of the legend handle to be 0.3
# SOLUTION START
| plt.plot(x, y, label="Line")
plt.legend(handlelength=0.3) | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(x,... | 633 | 122 | Matplotlib | 1 | Semantic | 121 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
```
Please help me to:
- Plot y over x with a legend of "Line"
- Adjust the length of the legend handle to be 0.3
- save the figure using `plt.savefig('output.png', bbox_inches ='tight... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(x,... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
plt.plot(x, y, label="Line")
plt.legend(handlelength=0.3)
plt.savefig('output.png', bbox_inches ='tight')
result = None
return result |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
plt.plot(x, y, label="Line")
plt.plot(y, x, label="Flipped")
# Show a two columns legend of this plot
# SOLUTION START
| plt.legend(ncol=2) | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(x,... | 634 | 123 | Matplotlib | 1 | Semantic | 121 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
plt.plot(x, y, label="Line")
plt.plot(y, x, label="Flipped")
```
Please help me to:
- Show a two columns legend of this plot
- save the figure using `plt.savefig('output.png', bbox_inch... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(x,... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
plt.plot(x, y, label="Line")
plt.plot(y, x, label="Flipped")
plt.legend(ncol=2)
plt.savefig('output.png', bbox_inches ='tight')
result = None
... |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
plt.plot(x, y, marker="*", label="Line")
# Show a legend of this plot and show two markers on the line
# SOLUTION START
| plt.legend(numpoints=2) | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(x,... | 635 | 124 | Matplotlib | 1 | Semantic | 121 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
plt.plot(x, y, marker="*", label="Line")
```
Please help me to:
- Show a legend of this plot and show two markers on the line
- save the figure using `plt.savefig('output.png', bbox_inc... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(x,... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
plt.plot(x, y, marker="*", label="Line")
plt.legend(numpoints=2)
plt.savefig('output.png', bbox_inches ='tight')
result = None
return resu... |
import matplotlib.pyplot as plt
import numpy as np
data = np.random.random((10, 10))
# plot the 2d matrix data with a colorbar
# SOLUTION START
| plt.imshow(data)
plt.colorbar() | import matplotlib.pyplot as plt
import numpy as np
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
data = np.random.random((10, 10))
plt.imshow(data)
plt.colorbar()
... | 636 | 125 | Matplotlib | 1 | Origin | 125 | Given this code block:
```
import matplotlib.pyplot as plt
import numpy as np
data = np.random.random((10, 10))
```
Please help me to:
- plot the 2d matrix data with a colorbar
- save the figure using `plt.savefig('output.png', bbox_inches ='tight')`
I need the solution to fit in a function with the following signat... | import matplotlib.pyplot as plt
import numpy as np
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
data = np.random.random((10, 10))
plt.imshow(data)
plt.colorbar()
... |
def solve(test_input):
import matplotlib.pyplot as plt
import numpy as np
data = np.random.random((10, 10))
plt.imshow(data)
plt.colorbar()
plt.savefig('output.png', bbox_inches ='tight')
result = None
return result |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
# Plot y over x. Give the plot a title "Figure 1". bold the word "Figure" in the title but do not bold "1"
# SOLUTION START
| plt.plot(x, y)
plt.title(r"$\bf{Figure}$ 1") | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(x,... | 637 | 126 | Matplotlib | 1 | Origin | 126 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
```
Please help me to:
- Plot y over x. Give the plot a title "Figure 1". bold the word "Figure" in the title but do not bold "1"
- save the figure using `plt.savefig('output.png', bbox... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(x,... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
plt.plot(x, y)
plt.title(r"$\bf{Figure}$ 1")
plt.savefig('output.png', bbox_inches ='tight')
result = None
return result |
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
df = pd.DataFrame(
{
"id": ["1", "2", "1", "2", "2"],
"x": [123, 22, 356, 412, 54],
"y": [120, 12, 35, 41, 45],
}
)
# Use seaborn to make a pairplot of data in `df` using `x` for x_vars, `y` for y_vars, and `id` ... | g = sns.pairplot(df, x_vars=["x"], y_vars=["y"], hue="id")
g._legend.remove() | import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
from PIL import Image
import numpy as np
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
df = pd.DataFrame(
{
... | 638 | 127 | Matplotlib | 1 | Origin | 127 | Given this code block:
```
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
df = pd.DataFrame(
{
"id": ["1", "2", "1", "2", "2"],
"x": [123, 22, 356, 412, 54],
"y": [120, 12, 35, 41, 45],
}
)
```
Please help me to:
- Use seaborn to make a pairplot of data in `df... | import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
from PIL import Image
import numpy as np
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
df = pd.DataFrame(
{
... |
def solve(test_input):
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
df = pd.DataFrame(
{
"id": ["1", "2", "1", "2", "2"],
"x": [123, 22, 356, 412, 54],
"y": [120, 12, 35, 41, 45],
}
)
g = sns.pairplot(df, x_v... |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
# Plot y over x and invert the x axis
# SOLUTION START
| plt.plot(x, y)
plt.gca().invert_xaxis() | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(x,... | 639 | 128 | Matplotlib | 1 | Origin | 128 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
```
Please help me to:
- Plot y over x and invert the x axis
- save the figure using `plt.savefig('output.png', bbox_inches ='tight')`
I need the solution to fit in a function with th... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(x,... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
plt.plot(x, y)
plt.gca().invert_xaxis()
plt.savefig('output.png', bbox_inches ='tight')
result = None
return result |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(11)
y = np.arange(11)
plt.xlim(0, 10)
plt.ylim(0, 10)
# Plot a scatter plot x over y and set both the x limit and y limit to be between 0 and 10
# Turn off axis clipping so data points can go beyond the axes
# SOLUTION START
| plt.scatter(x, y, clip_on=False) | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(11)
y = np.arange(11)
plt.xlim(0,... | 640 | 129 | Matplotlib | 1 | Origin | 129 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(11)
y = np.arange(11)
plt.xlim(0, 10)
plt.ylim(0, 10)
```
Please help me to:
- Plot a scatter plot x over y and set both the x limit and y limit to be between 0 and 10
- Turn off axis clipping so data point... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(11)
y = np.arange(11)
plt.xlim(0,... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(11)
y = np.arange(11)
plt.xlim(0, 10)
plt.ylim(0, 10)
plt.scatter(x, y, clip_on=False)
plt.savefig('output.png', bbox_inches ='tight')
result = None
return ... |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
# Plot a scatter plot with values in x and y
# Plot the data points to have red inside and have black border
# SOLUTION START
| plt.scatter(x, y, c="red", edgecolors="black") | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.scatter... | 641 | 130 | Matplotlib | 1 | Origin | 130 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
```
Please help me to:
- Plot a scatter plot with values in x and y
- Plot the data points to have red inside and have black border
- save the figure using `plt.savefig('output.png', b... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.scatter... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
plt.scatter(x, y, c="red", edgecolors="black")
plt.savefig('output.png', bbox_inches ='tight')
result = None
return result |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
# plot y over x on a 2 by 2 subplots with a figure size of (15, 15)
# repeat the plot in each subplot
# SOLUTION START
| f, axs = plt.subplots(2, 2, figsize=(15, 15))
for ax in f.axes:
ax.plot(x, y) | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
f, axs = pl... | 642 | 131 | Matplotlib | 1 | Origin | 131 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
```
Please help me to:
- plot y over x on a 2 by 2 subplots with a figure size of (15, 15)
- repeat the plot in each subplot
- save the figure using `plt.savefig('output.png', bbox_inc... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
f, axs = pl... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
f, axs = plt.subplots(2, 2, figsize=(15, 15))
for ax in f.axes:
ax.plot(x, y)
plt.savefig('output.png', bbox_inches ='tight')
result = None... |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.random.rand(100) * 10
# Make a histogram of x
# Make the histogram range from 0 to 10
# Make bar width 2 for each bar in the histogram and have 5 bars in total
# SOLUTION START
| plt.hist(x, bins=np.arange(0, 11, 2)) | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.random.rand(100) * 10
plt.hist(x, bins=np.ar... | 643 | 132 | Matplotlib | 1 | Origin | 132 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.random.rand(100) * 10
```
Please help me to:
- Make a histogram of x
- Make the histogram range from 0 to 10
- Make bar width 2 for each bar in the histogram and have 5 bars in total
- save the figure using `plt.... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.random.rand(100) * 10
plt.hist(x, bins=np.ar... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.random.rand(100) * 10
plt.hist(x, bins=np.arange(0, 11, 2))
plt.savefig('output.png', bbox_inches ='tight')
result = None
return result |
from matplotlib import pyplot as plt
import numpy as np
x = np.arange(10)
y = np.arange(1, 11)
error = np.random.random(y.shape)
# Plot y over x and show the error according to `error`
# Plot the error as a shaded region rather than error bars
# SOLUTION START
| plt.plot(x, y, "k-")
plt.fill_between(x, y - error, y + error) | from matplotlib import pyplot as plt
import numpy as np
from PIL import Image
import matplotlib
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(1, 11)
error... | 644 | 133 | Matplotlib | 1 | Origin | 133 | Given this code block:
```
from matplotlib import pyplot as plt
import numpy as np
x = np.arange(10)
y = np.arange(1, 11)
error = np.random.random(y.shape)
```
Please help me to:
- Plot y over x and show the error according to `error`
- Plot the error as a shaded region rather than error bars
- save the figure using ... | from matplotlib import pyplot as plt
import numpy as np
from PIL import Image
import matplotlib
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(1, 11)
error... |
def solve(test_input):
from matplotlib import pyplot as plt
import numpy as np
x = np.arange(10)
y = np.arange(1, 11)
error = np.random.random(y.shape)
plt.plot(x, y, "k-")
plt.fill_between(x, y - error, y + error)
plt.savefig('output.png', bbox_inches ='tight')
result = None
... |
import matplotlib.pyplot as plt
import numpy as np
xvec = np.linspace(-5.0, 5.0, 100)
x, y = np.meshgrid(xvec, xvec)
z = -np.hypot(x, y)
plt.contourf(x, y, z)
# draw x=0 and y=0 axis in my contour plot with white color
# SOLUTION START
| plt.axhline(0, color="white")
plt.axvline(0, color="white") | import matplotlib.pyplot as plt
import numpy as np
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
xvec = np.linspace(-5.0, 5.0, 100)
x, y = np.meshgrid(xvec, xvec)
z... | 645 | 134 | Matplotlib | 1 | Origin | 134 | Given this code block:
```
import matplotlib.pyplot as plt
import numpy as np
xvec = np.linspace(-5.0, 5.0, 100)
x, y = np.meshgrid(xvec, xvec)
z = -np.hypot(x, y)
plt.contourf(x, y, z)
```
Please help me to:
- draw x=0 and y=0 axis in my contour plot with white color
- save the figure using `plt.savefig('output.png',... | import matplotlib.pyplot as plt
import numpy as np
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
xvec = np.linspace(-5.0, 5.0, 100)
x, y = np.meshgrid(xvec, xvec)
z... |
def solve(test_input):
import matplotlib.pyplot as plt
import numpy as np
xvec = np.linspace(-5.0, 5.0, 100)
x, y = np.meshgrid(xvec, xvec)
z = -np.hypot(x, y)
plt.contourf(x, y, z)
plt.axhline(0, color="white")
plt.axvline(0, color="white")
plt.savefig('output.png', bbox_inch... |
import matplotlib.pyplot as plt
import numpy as np
box_position, box_height, box_errors = np.arange(4), np.ones(4), np.arange(1, 5)
c = ["r", "r", "b", "b"]
fig, ax = plt.subplots()
ax.bar(box_position, box_height, color="yellow")
# Plot error bars with errors specified in box_errors. Use colors in c to color the err... | for pos, y, err, color in zip(box_position, box_height, box_errors, c):
ax.errorbar(pos, y, err, color=color) | import matplotlib.pyplot as plt
import numpy as np
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
box_position, box_height, box_errors = np.arange(4), np.ones(4), np.arange(... | 646 | 135 | Matplotlib | 1 | Origin | 135 | Given this code block:
```
import matplotlib.pyplot as plt
import numpy as np
box_position, box_height, box_errors = np.arange(4), np.ones(4), np.arange(1, 5)
c = ["r", "r", "b", "b"]
fig, ax = plt.subplots()
ax.bar(box_position, box_height, color="yellow")
```
Please help me to:
- Plot error bars with errors specifie... | import matplotlib.pyplot as plt
import numpy as np
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
box_position, box_height, box_errors = np.arange(4), np.ones(4), np.arange(... |
def solve(test_input):
import matplotlib.pyplot as plt
import numpy as np
box_position, box_height, box_errors = np.arange(4), np.ones(4), np.arange(1, 5)
c = ["r", "r", "b", "b"]
fig, ax = plt.subplots()
ax.bar(box_position, box_height, color="yellow")
for pos, y, err, color in zip(b... |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
z = np.arange(10)
a = np.arange(10)
# Plot y over x and z over a in two side-by-side subplots
# Make "Y" the title of the first subplot and "Z" the title of the second subplot
# Raise the title of the second sub... | fig, (ax1, ax2) = plt.subplots(1, 2, sharey=True)
ax1.plot(x, y)
ax1.set_title("Y")
ax2.plot(a, z)
ax2.set_title("Z", y=1.08) | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
z = np.aran... | 647 | 136 | Matplotlib | 1 | Origin | 136 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
z = np.arange(10)
a = np.arange(10)
```
Please help me to:
- Plot y over x and z over a in two side-by-side subplots
- Make "Y" the title of the first subplot and "Z" the title of the ... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
z = np.aran... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
z = np.arange(10)
a = np.arange(10)
fig, (ax1, ax2) = plt.subplots(1, 2, sharey=True)
ax1.plot(x, y)
ax1.set_title("Y")
ax2.plot(a, z)
... |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
# make 4 by 4 subplots with a figure size (5,5)
# in each subplot, plot y over x and show axis tick labels
# give enough spacing between subplots so the tick labels don't overlap
# SOLUTION START
| fig, axes = plt.subplots(nrows=4, ncols=4, figsize=(5, 5))
for ax in axes.flatten():
ax.plot(x, y)
fig.tight_layout() | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
fig, axes =... | 648 | 137 | Matplotlib | 1 | Origin | 137 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
```
Please help me to:
- make 4 by 4 subplots with a figure size (5,5)
- in each subplot, plot y over x and show axis tick labels
- give enough spacing between subplots so the tick la... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
fig, axes =... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
fig, axes = plt.subplots(nrows=4, ncols=4, figsize=(5, 5))
for ax in axes.flatten():
ax.plot(x, y)
fig.tight_layout()
plt.savefig('output.p... |
import matplotlib.pyplot as plt
import numpy as np
d = np.random.random((10, 10))
# Use matshow to plot d and make the figure size (8, 8)
# SOLUTION START
| matfig = plt.figure(figsize=(8, 8))
plt.matshow(d, fignum=matfig.number) | import matplotlib.pyplot as plt
import numpy as np
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
d = np.random.random((10, 10))
matfig = plt.figure(figsize=(8, 8))
... | 649 | 138 | Matplotlib | 1 | Origin | 138 | Given this code block:
```
import matplotlib.pyplot as plt
import numpy as np
d = np.random.random((10, 10))
```
Please help me to:
- Use matshow to plot d and make the figure size (8, 8)
- save the figure using `plt.savefig('output.png', bbox_inches ='tight')`
I need the solution to fit in a function with the follo... | import matplotlib.pyplot as plt
import numpy as np
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
d = np.random.random((10, 10))
matfig = plt.figure(figsize=(8, 8))
... |
def solve(test_input):
import matplotlib.pyplot as plt
import numpy as np
d = np.random.random((10, 10))
matfig = plt.figure(figsize=(8, 8))
plt.matshow(d, fignum=matfig.number)
plt.savefig('output.png', bbox_inches ='tight')
result = None
return result |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df = sns.load_dataset("penguins")[
["bill_length_mm", "bill_depth_mm", "flipper_length_mm", "body_mass_g"]
].head(10)
# Plot df as a matplotlib table. Set the bbox of the table to [0, 0, 1, 1]
# SOLUTION START
| bbox = [0, 0, 1, 1]
plt.table(cellText=df.values, rowLabels=df.index, bbox=bbox, colLabels=df.columns) | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from PIL import Image
import matplotlib
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
df = sns.load_d... | 650 | 139 | Matplotlib | 1 | Origin | 139 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df = sns.load_dataset("penguins")[
["bill_length_mm", "bill_depth_mm", "flipper_length_mm", "body_mass_g"]
].head(10)
```
Please help me to:
- Plot df as a matplotlib table. Set the bbox of the t... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from PIL import Image
import matplotlib
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
df = sns.load_d... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df = sns.load_dataset("penguins")[
["bill_length_mm", "bill_depth_mm", "flipper_length_mm", "body_mass_g"]
].head(10)
bbox = [0, 0, 1, 1]
plt.table(cellText=... |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
# Plot y over x in a line chart. Show x axis tick labels on both top and bottom of the figure.
# SOLUTION START
| plt.plot(x, y)
plt.tick_params(labeltop=True) | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(x,... | 651 | 140 | Matplotlib | 1 | Origin | 140 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
```
Please help me to:
- Plot y over x in a line chart. Show x axis tick labels on both top and bottom of the figure.
- save the figure using `plt.savefig('output.png', bbox_inches ='ti... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(x,... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
plt.plot(x, y)
plt.tick_params(labeltop=True)
plt.savefig('output.png', bbox_inches ='tight')
result = None
return result |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
# Plot y over x in a line chart. Show x axis ticks on both top and bottom of the figure.
# SOLUTION START
| plt.plot(x, y)
plt.tick_params(top=True) | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(x,... | 652 | 141 | Matplotlib | 1 | Semantic | 140 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
```
Please help me to:
- Plot y over x in a line chart. Show x axis ticks on both top and bottom of the figure.
- save the figure using `plt.savefig('output.png', bbox_inches ='tight')`... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(x,... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
plt.plot(x, y)
plt.tick_params(top=True)
plt.savefig('output.png', bbox_inches ='tight')
result = None
return result |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
# Plot y over x in a line chart. Show x axis tick labels but hide the x axis ticks
# SOLUTION START
| plt.plot(x, y)
plt.tick_params(bottom=False, labelbottom=True) | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(x,... | 653 | 142 | Matplotlib | 1 | Semantic | 140 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
```
Please help me to:
- Plot y over x in a line chart. Show x axis tick labels but hide the x axis ticks
- save the figure using `plt.savefig('output.png', bbox_inches ='tight')`
I n... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(x,... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
plt.plot(x, y)
plt.tick_params(bottom=False, labelbottom=True)
plt.savefig('output.png', bbox_inches ='tight')
result = None
return result |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df = sns.load_dataset("exercise")
# Make catplots of scatter plots by using "time" as x, "pulse" as y, "kind" as hue, and "diet" as col
# Change the subplots titles to "Group: Fat" and "Group: No Fat"
# SOLUTION START
| g = sns.catplot(x="time", y="pulse", hue="kind", col="diet", data=df)
axs = g.axes.flatten()
axs[0].set_title("Group: Fat")
axs[1].set_title("Group: No Fat") | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from PIL import Image
import matplotlib
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
df = sns.load_d... | 654 | 143 | Matplotlib | 1 | Origin | 143 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df = sns.load_dataset("exercise")
```
Please help me to:
- Make catplots of scatter plots by using "time" as x, "pulse" as y, "kind" as hue, and "diet" as col
- Change the subplots titles to "Group:... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from PIL import Image
import matplotlib
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
df = sns.load_d... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df = sns.load_dataset("exercise")
g = sns.catplot(x="time", y="pulse", hue="kind", col="diet", data=df)
axs = g.axes.flatten()
axs[0].set_title("Group: Fat")
axs... |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df = sns.load_dataset("exercise")
# Make catplots of scatter plots by using "time" as x, "pulse" as y, "kind" as hue, and "diet" as col
# Change the xlabels to "Exercise Time" and "Exercise Time"
# SOLUTION START
| g = sns.catplot(x="time", y="pulse", hue="kind", col="diet", data=df)
axs = g.axes.flatten()
axs[0].set_xlabel("Exercise Time")
axs[1].set_xlabel("Exercise Time") | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
df = sns.load_dataset("exercise")... | 655 | 144 | Matplotlib | 1 | Semantic | 143 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df = sns.load_dataset("exercise")
```
Please help me to:
- Make catplots of scatter plots by using "time" as x, "pulse" as y, "kind" as hue, and "diet" as col
- Change the xlabels to "Exercise Time"... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
df = sns.load_dataset("exercise")... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df = sns.load_dataset("exercise")
g = sns.catplot(x="time", y="pulse", hue="kind", col="diet", data=df)
axs = g.axes.flatten()
axs[0].set_xlabel("Exercise Time")
... |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df = sns.load_dataset("exercise")
# Make catplots of scatter plots by using "time" as x, "pulse" as y, "kind" as hue, and "diet" as col
# Do not show any ylabel on either subplot
# SOLUTION START
| g = sns.catplot(x="time", y="pulse", hue="kind", col="diet", data=df)
axs = g.axes.flatten()
axs[0].set_ylabel("") | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
df = sns.load_dataset("exercise")... | 656 | 145 | Matplotlib | 1 | Semantic | 143 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df = sns.load_dataset("exercise")
```
Please help me to:
- Make catplots of scatter plots by using "time" as x, "pulse" as y, "kind" as hue, and "diet" as col
- Do not show any ylabel on either subp... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
df = sns.load_dataset("exercise")... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df = sns.load_dataset("exercise")
g = sns.catplot(x="time", y="pulse", hue="kind", col="diet", data=df)
axs = g.axes.flatten()
axs[0].set_ylabel("")
plt.savefig(... |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
# plot y over x with label "y"
# make the legend fontsize 8
# SOLUTION START
| plt.plot(y, x, label="y")
plt.legend(fontsize=8) | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(y,... | 657 | 146 | Matplotlib | 1 | Origin | 146 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
```
Please help me to:
- plot y over x with label "y"
- make the legend fontsize 8
- save the figure using `plt.savefig('output.png', bbox_inches ='tight')`
I need the solution to fi... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(y,... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
plt.plot(y, x, label="y")
plt.legend(fontsize=8)
plt.savefig('output.png', bbox_inches ='tight')
result = None
return result |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
# Plot y over x with figsize (5, 5) and dpi 300
# SOLUTION START
| plt.figure(figsize=(5, 5), dpi=300)
plt.plot(y, x) | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.figure(... | 658 | 147 | Matplotlib | 1 | Origin | 147 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
```
Please help me to:
- Plot y over x with figsize (5, 5) and dpi 300
- save the figure using `plt.savefig('output.png', bbox_inches ='tight')`
I need the solution to fit in a functi... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.figure(... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
plt.figure(figsize=(5, 5), dpi=300)
plt.plot(y, x)
plt.savefig('output.png', bbox_inches ='tight')
result = None
return result |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
# Plot y over x with label "y" and show legend
# Remove the border of frame of legend
# SOLUTION START
| plt.plot(y, x, label="y")
plt.legend(frameon=False) | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(y,... | 659 | 148 | Matplotlib | 1 | Origin | 148 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
```
Please help me to:
- Plot y over x with label "y" and show legend
- Remove the border of frame of legend
- save the figure using `plt.savefig('output.png', bbox_inches ='tight')`
... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
plt.plot(y,... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
plt.plot(y, x, label="y")
plt.legend(frameon=False)
plt.savefig('output.png', bbox_inches ='tight')
result = None
return result |
import numpy as np
import math
import matplotlib
import matplotlib.pyplot as plt
t = np.linspace(0, 2 * math.pi, 400)
a = np.sin(t)
b = np.cos(t)
c = a + b
# Plot a, b, c in the same figure
# SOLUTION START
| plt.plot(t, a, t, b, t, c) | import numpy as np
import math
import matplotlib
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
t = np.linspace(0, 2 * math.pi, 400)
a = ... | 660 | 149 | Matplotlib | 1 | Origin | 149 | Given this code block:
```
import numpy as np
import math
import matplotlib
import matplotlib.pyplot as plt
t = np.linspace(0, 2 * math.pi, 400)
a = np.sin(t)
b = np.cos(t)
c = a + b
```
Please help me to:
- Plot a, b, c in the same figure
- save the figure using `plt.savefig('output.png', bbox_inches ='tight')`
I n... | import numpy as np
import math
import matplotlib
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
t = np.linspace(0, 2 * math.pi, 400)
a = ... |
def solve(test_input):
import numpy as np
import math
import matplotlib
import matplotlib.pyplot as plt
t = np.linspace(0, 2 * math.pi, 400)
a = np.sin(t)
b = np.cos(t)
c = a + b
plt.plot(t, a, t, b, t, c)
plt.savefig('output.png', bbox_inches ='tight')
result = None
... |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df = sns.load_dataset("penguins")[["bill_length_mm", "species", "sex"]]
# Make a stripplot for the data in df. Use "sex" as x, "bill_length_mm" as y, and "species" for the color
# Remove the legend from the stripplot
# SOLUTI... | ax = sns.stripplot(x="sex", y="bill_length_mm", hue="species", data=df)
ax.legend_.remove() | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
df = sns.load_dataset("penguins")... | 661 | 150 | Matplotlib | 1 | Origin | 150 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df = sns.load_dataset("penguins")[["bill_length_mm", "species", "sex"]]
```
Please help me to:
- Make a stripplot for the data in df. Use "sex" as x, "bill_length_mm" as y, and "species" for the colo... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
df = sns.load_dataset("penguins")... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df = sns.load_dataset("penguins")[["bill_length_mm", "species", "sex"]]
ax = sns.stripplot(x="sex", y="bill_length_mm", hue="species", data=df)
ax.legend_.remove()
p... |
import seaborn as sns
import matplotlib.pylab as plt
import pandas
import numpy as np
df = pandas.DataFrame(
{
"a": np.arange(1, 31),
"b": ["A",] * 10 + ["B",] * 10 + ["C",] * 10,
"c": np.random.rand(30),
}
)
# Use seaborn FaceGrid for rows in "b" and plot seaborn pointplots of "c" ove... | g = sns.FacetGrid(df, row="b")
g.map(sns.pointplot, "a", "c")
for ax in g.axes.flat:
labels = ax.get_xticklabels() # get x labels
for i, l in enumerate(labels):
if i % 2 == 0:
labels[i] = "" # skip even labels
ax.set_xticklabels(labels) # set new labels | import seaborn as sns
import matplotlib.pylab as plt
import pandas
import numpy as np
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
df = pandas.DataFrame(
{
... | 662 | 151 | Matplotlib | 1 | Origin | 151 | Given this code block:
```
import seaborn as sns
import matplotlib.pylab as plt
import pandas
import numpy as np
df = pandas.DataFrame(
{
"a": np.arange(1, 31),
"b": ["A",] * 10 + ["B",] * 10 + ["C",] * 10,
"c": np.random.rand(30),
}
)
```
Please help me to:
- Use seaborn FaceGrid for r... | import seaborn as sns
import matplotlib.pylab as plt
import pandas
import numpy as np
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
df = pandas.DataFrame(
{
... |
def solve(test_input):
import seaborn as sns
import matplotlib.pylab as plt
import pandas
import numpy as np
df = pandas.DataFrame(
{
"a": np.arange(1, 31),
"b": ["A",] * 10 + ["B",] * 10 + ["C",] * 10,
"c": np.random.rand(30),
}
)
g... |
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
x = np.random.random(10)
y = np.random.random(10)
z = np.random.random(10)
# Make a 3D scatter plot of x,y,z
# change the view of the plot to have 100 azimuth and 50 elevation
# SOLUTION START
| fig = plt.figure()
ax = fig.add_subplot(111, projection="3d")
ax.scatter(x, y, z)
ax.azim = 100
ax.elev = 50 | import matplotlib.pyplot as plt
import numpy as np
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.random.random(10)
y = np.random.random(10)
z = np.random.ran... | 663 | 152 | Matplotlib | 1 | Origin | 152 | Given this code block:
```
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
x = np.random.random(10)
y = np.random.random(10)
z = np.random.random(10)
```
Please help me to:
- Make a 3D scatter plot of x,y,z
- change the view of the plot to have 100 azimuth and 50 elevation
-... | import matplotlib.pyplot as plt
import numpy as np
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.random.random(10)
y = np.random.random(10)
z = np.random.ran... |
def solve(test_input):
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
x = np.random.random(10)
y = np.random.random(10)
z = np.random.random(10)
fig = plt.figure()
ax = fig.add_subplot(111, projection="3d")
ax.scatter(x, y, z)
ax... |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
# Plot y over x in a line chart and name axis with labels ("x" and "y")
# Hide tick labels but keep axis labels
# SOLUTION START
| fig, ax = plt.subplots()
ax.plot(x, y)
ax.set_xticklabels([])
ax.set_yticklabels([])
ax.set_xlabel("x")
ax.set_ylabel("y") | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
fig, ax = p... | 664 | 153 | Matplotlib | 1 | Origin | 153 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
```
Please help me to:
- Plot y over x in a line chart and name axis with labels ("x" and "y")
- Hide tick labels but keep axis labels
- save the figure using `plt.savefig('output.png'... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.arange(10)
y = np.arange(10)
fig, ax = p... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.arange(10)
y = np.arange(10)
fig, ax = plt.subplots()
ax.plot(x, y)
ax.set_xticklabels([])
ax.set_yticklabels([])
ax.set_xlabel("x")
ax.set_ylabel("y")
plt.savefig(... |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.random.random((10, 10))
from matplotlib import gridspec
nrow = 2
ncol = 2
fig = plt.figure(figsize=(ncol + 1, nrow + 1))
# Make a 2x2 subplots with fig and plot x in each subplot as an image
# Remove the space between each subplot and mak... | gs = gridspec.GridSpec(
nrow,
ncol,
wspace=0.0,
hspace=0.0,
top=1.0 - 0.5 / (nrow + 1),
bottom=0.5 / (nrow + 1),
left=0.5 / (ncol + 1),
right=1 - 0.5 / (ncol + 1),
)
for i in range(nrow):
for j in range(ncol):
ax = plt.subplot(gs[i, j])
ax.imshow(x)
ax.set_xt... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib import gridspec
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.random.random((1... | 665 | 154 | Matplotlib | 1 | Origin | 154 | Given this code block:
```
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.random.random((10, 10))
from matplotlib import gridspec
nrow = 2
ncol = 2
fig = plt.figure(figsize=(ncol + 1, nrow + 1))
```
Please help me to:
- Make a 2x2 subplots with fig and plot x in each subplot as an image
... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib import gridspec
from PIL import Image
def skip_plt_cmds(l):
return all(
p not in l for p in ["plt.show()", "plt.clf()", "plt.close()", "savefig"]
)
def generate_test_case(test_case_id):
x = np.random.random((1... |
def solve(test_input):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
x = np.random.random((10, 10))
from matplotlib import gridspec
nrow = 2
ncol = 2
fig = plt.figure(figsize=(ncol + 1, nrow + 1))
gs = gridspec.GridSpec(
nrow,
ncol,
... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.