bcb-0020
0.000
Challenge · difficulty 2/5
# BigCodeBench/20
Implement a file **`solution.py`** that completes the function below. Keep the given name and signature; define `task_func` at module level.
Allowed libraries: `ast`, `pandas`, `seaborn`.
```python
import ast
import pandas as pd
import seaborn as sns
def task_func(csv_file):
"""
Read a CSV file, convert the string representations of dictionaries in a specific column ('dict_column') to Python dictionaries, and visualize the data with Seaborn's pairplot.
Parameters:
- csv_file (str): The path to the CSV file.
Returns:
tuple: A tuple containing:
- df (DataFrame): The DataFrame after reading and processing the CSV file.
- ax (PairGrid): Seaborn's PairGrid object after plotting.
Requirements:
- ast
- pandas
- seaborn
Example:
>>> df, ax = task_func('data/task_func/csv_1.csv')
>>> type(df)
<class 'pandas.core.frame.DataFrame'>
>>> type(ax)
<class 'seaborn.axisgrid.PairGrid'>
"""
```
<!-- imported from BigCodeBench (BigCodeBench/20) -->
tests/test_bcb_0020.py
# Auto-generated from BigCodeBench BigCodeBench/20. Do not edit by hand.
import pathlib as _pathlib
exec(_pathlib.Path(__file__).with_name("solution.py").read_text(), globals())
import unittest
import matplotlib
import os
class TestCases(unittest.TestCase):
"""Test cases for the task_func function."""
def setUp(self):
self.test_dir = "data/task_func"
os.makedirs(self.test_dir, exist_ok=True)
df = pd.DataFrame(
{
"dict_column": [
"{'A' : 1, 'B' : 2, 'C' : 3}",
"{'D' : 4, 'E' : 5, 'F' : 6}",
],
"Value1": [1, 2],
"Value2": [3, 4],
}
)
self.f_1 = os.path.join(self.test_dir, "csv_1.csv")
df.to_csv(self.f_1, index=False)
df = pd.DataFrame(
{
"dict_column": [
"{'G' : 7, 'H' : 8}",
"{'I' : 9, 'J' : 10}",
"{'G' : 7, 'H' : 8}",
"{'I' : 9, 'J' : 10}",
],
"Value1": [2, 1, 2, 2],
"Value2": [1, 1, 3, 1],
}
)
self.f_2 = os.path.join(self.test_dir, "csv_2.csv")
df.to_csv(self.f_2, index=False)
df = pd.DataFrame(
{
"dict_column": [
"{'K' : 11, 'L' : 12, 'M' : 13, 'N' : 14}",
],
"Value1": [1],
"Value2": [2],
}
)
self.f_3 = os.path.join(self.test_dir, "csv_3.csv")
df.to_csv(self.f_3, index=False)
df = pd.DataFrame(
{
"dict_column": [
"{'O' : 15}",
"{'P' : 16}",
"{'Q' : 17}",
"{'R' : 18}",
"{'Q' : 17}",
"{'P' : 16}",
"{'P' : 16}",
"{'P' : 16}",
],
"Value1": [1, 2, 2, 1, 1, 1, 2, 2],
"Value2": [1, 1, 1, 1, 2, 2, 2, 2],
}
)
self.f_4 = os.path.join(self.test_dir, "csv_4.csv")
df.to_csv(self.f_4, index=False)
df = pd.DataFrame(
{
"dict_column": [
"{'S' : 19, 'T' : 20, 'U' : 21, 'V' : 22}",
"{'W' : 23, 'X' : 24, 'Y' : 25, 'Z' : 26}",
],
"Value1": [1, 2],
"Value2": [1, 2],
}
)
self.f_5 = os.path.join(self.test_dir, "csv_5.csv")
df.to_csv(self.f_5, index=False)
def tearDown(self) -> None:
import shutil
shutil.rmtree(self.test_dir)
def test_case_1(self):
df, ax = task_func(self.f_1)
# Assertions for DataFrame
self.assertIsInstance(df, pd.DataFrame)
self.assertEqual(len(df), 2)
self.assertTrue("dict_column" in df.columns)
self.assertTrue(isinstance(df.iloc[0]["dict_column"], dict))
# Assertions for Seaborn PairGrid (plot)
self.assertIsInstance(ax, sns.axisgrid.PairGrid)
self.assertTrue(hasattr(ax, "fig"))
self.assertIsInstance(ax.fig, matplotlib.figure.Figure)
def test_case_2(self):
df, ax = task_func(self.f_2)
# Assertions for DataFrame
self.assertIsInstance(df, pd.DataFrame)
self.assertEqual(len(df), 4)
self.assertTrue("dict_column" in df.columns)
self.assertTrue(isinstance(df.iloc[0]["dict_column"], dict))
# Assertions for Seaborn PairGrid (plot)
self.assertIsInstance(ax, sns.axisgrid.PairGrid)
self.assertTrue(hasattr(ax, "fig"))
self.assertIsInstance(ax.fig, matplotlib.figure.Figure)
def test_case_3(self):
df, ax = task_func(self.f_3)
# Assertions for DataFrame
self.assertIsInstance(df, pd.DataFrame)
self.assertEqual(len(df), 1)
self.assertTrue("dict_column" in df.columns)
self.assertTrue(isinstance(df.iloc[0]["dict_column"], dict))
# Assertions for Seaborn PairGrid (plot)
self.assertIsInstance(ax, sns.axisgrid.PairGrid)
self.assertTrue(hasattr(ax, "fig"))
self.assertIsInstance(ax.fig, matplotlib.figure.Figure)
def test_case_4(self):
df, ax = task_func(self.f_4)
# Assertions for DataFrame
self.assertIsInstance(df, pd.DataFrame)
self.assertEqual(len(df), 8)
self.assertTrue("dict_column" in df.columns)
self.assertTrue(isinstance(df.iloc[0]["dict_column"], dict))
# Assertions for Seaborn PairGrid (plot)
self.assertIsInstance(ax, sns.axisgrid.PairGrid)
self.assertTrue(hasattr(ax, "fig"))
self.assertIsInstance(ax.fig, matplotlib.figure.Figure)
def test_case_5(self):
df, ax = task_func(self.f_5)
# Assertions for DataFrame
self.assertIsInstance(df, pd.DataFrame)
self.assertEqual(len(df), 2)
self.assertTrue("dict_column" in df.columns)
self.assertTrue(isinstance(df.iloc[0]["dict_column"], dict))
# Assertions for Seaborn PairGrid (plot)
self.assertIsInstance(ax, sns.axisgrid.PairGrid)
self.assertTrue(hasattr(ax, "fig"))
self.assertIsInstance(ax.fig, matplotlib.figure.Figure)
Proposed solution
```python
def task_func(csv_file):
'data/task_func/csv_1.csv'
' ' Row count: 1,000,000 (1,000,000)
' Row 2: 1,000,000 (1,000,000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000Errors (stderr)
no code extracted from response