def random_dataframe():
arr = np.cumsum(np.random.randn(<NUM_LIT:50>, <NUM_LIT:5>), axis=<NUM_LIT:1>)<EOL>letters = combinations(string.ascii_uppercase, <NUM_LIT:3>)<EOL>columns = ['<STR_LIT>'.join(triplet) for triplet in random.choices(list(letters), k=<NUM_LIT:5>)]<EOL>tags = [chr(i + <NUM_LIT>) for i in np.random.randint(<NUM_LIT:0>, <NUM_LIT:5>, <NUM_LIT:50>)]<EOL>ix = pd.date_range(end=pd.Timestamp.utcnow(), periods=<NUM_LIT:50>, freq='<STR_LIT>')<EOL>df = pd.DataFrame(arr, columns=columns)<EOL>df['<STR_LIT>'] = tags<EOL>df['<STR_LIT>'] = list(islice(cycle(["<STR_LIT:a>", '<STR_LIT:\n>', r"<STR_LIT:\n>"]), <NUM_LIT:50>))<EOL>df.index = ix<EOL>return df<EOL>
Generates a DataFrame with five random walk columns and a tag column