[Bug]: Pandas Output: There was an error running the output as Python code. Error message: name 'p' is not defined

[uniltone]

Bug Description

I want to use pandas_query_engine to generate a statistical chart, but an error message is reported: name 'p' is not defined

Below is the code

import pandas as pd
from llama_index.experimental.query_engine import PandasQueryEngine
from llama_index.llms.openai import OpenAI
import os
df = pd.DataFrame(
{
"country": [
"United States",
"United Kingdom",
"France",
"Germany",
"Italy",
"Spain",
"Canada",
"Australia",
"Japan",
"China",
],
"gdp": [
21400000,
2940000,
2830000,
3870000,
2160000,
1350000,
1780000,
1320000,
516000,
14000000,
],
"happiness": [7.3, 7.2, 6.5, 7.0, 6.0, 6.3, 7.3, 7.3, 5.9, 5.0],
}
)

llm = OpenAI()
query_engine = PandasQueryEngine(df=df,verbose=True)
response = query_engine.query(
"Visualize barchat of number of happiness of country .",
)

Version

0.10.40

Steps to Reproduce

i don't kown

Relevant Logs/Tracbacks

error report：
> Pandas Instructions:


df.plot(kind='bar', x='country', y='happiness')

Traceback (most recent call last):
  File "E:\anaconda\Lib\site-packages\llama_index\experimental\query_engine\pandas\output_parser.py", line 54, in default_output_processor
    output_str = str(safe_eval(module_end_str, {"np": np, "pd": pd}, local_vars))#修改
                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "E:\anaconda\Lib\site-packages\llama_index\experimental\exec_utils.py", line 159, in safe_eval
    return eval(__source, _get_restricted_globals(__globals), __locals)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "<string>", line 1, in <module>
NameError: name 'p' is not defined
> Pandas Output: There was an error running the output as Python code. Error message: name 'p' is not defined

[dosubot]

To resolve the "name 'p' is not defined" error when generating a bar chart using pandas_query_engine, you need to ensure that the plotting library (likely matplotlib.pyplot as plt) is imported and used correctly. The provided code does not include any plotting logic, so you would need to add the necessary imports and plotting code.

Here is an example of how you can modify the code to include the plotting logic:

import pandas as pd
import matplotlib.pyplot as plt
from llama_index.experimental.query_engine import PandasQueryEngine
from llama_index.llms.openai import OpenAI

df = pd.DataFrame(
    {
        "country": [
            "United States",
            "United Kingdom",
            "France",
            "Germany",
            "Italy",
            "Spain",
            "Canada",
            "Australia",
            "Japan",
            "China",
        ],
        "gdp": [
            21400000,
            2940000,
            2830000,
            3870000,
            2160000,
            1350000,
            1780000,
            1320000,
            516000,
            14000000,
        ],
        "happiness": [7.3, 7.2, 6.5, 7.0, 6.0, 6.3, 7.3, 7.3, 5.9, 5.0],
    }
)

llm = OpenAI()
query_engine = PandasQueryEngine(df=df, verbose=True)
response = query_engine.query(
    "Visualize bar chart of number of happiness of country.",
)

# Plotting the bar chart
df.plot(kind='bar', x='country', y='happiness')
plt.xlabel('Country')
plt.ylabel('Happiness')
plt.title('Happiness by Country')
plt.show()

This code includes the necessary import for matplotlib.pyplot and adds the logic to generate a bar chart for the happiness of countries. Make sure to replace llm with the actual language model you are using if needed ^[1].

Details

About Dosu
This response is meant to be useful and save you time. It is not meant to be a precise solution, but rather a starting point for your own research.

Help me be more useful! Please leave a 👍 if this is helpful and 👎 if it is irrelevant.

To continue the conversation, mention @dosu.

[uniltone]

How to save the generated statistical chart@dosu.

[dosubot]

要保存生成的统计图，可以使用 matplotlib 库中的 plt.savefig 函数。以下是修改后的代码示例，展示如何保存生成的统计图：

import pandas as pd
import matplotlib.pyplot as plt
from llama_index.experimental.query_engine import PandasQueryEngine
from llama_index.llms.openai import OpenAI

df = pd.DataFrame(
    {
        "country": [
            "United States",
            "United Kingdom",
            "France",
            "Germany",
            "Italy",
            "Spain",
            "Canada",
            "Australia",
            "Japan",
            "China",
        ],
        "gdp": [
            21400000,
            2940000,
            2830000,
            3870000,
            2160000,
            1350000,
            1780000,
            1320000,
            516000,
            14000000,
        ],
        "happiness": [7.3, 7.2, 6.5, 7.0, 6.0, 6.3, 7.3, 7.3, 5.9, 5.0],
    }
)

llm = OpenAI()
query_engine = PandasQueryEngine(df=df, verbose=True)
response = query_engine.query(
    "Visualize bar chart of number of happiness of country.",
)

# 生成并保存柱状图
df.plot(kind='bar', x='country', y='happiness')
plt.xlabel('Country')
plt.ylabel('Happiness')
plt.title('Happiness by Country')
plt.savefig('happiness_by_country.png')  # 保存图表到文件
plt.show()

在这段代码中，plt.savefig('happiness_by_country.png') 用于将生成的图表保存到文件 happiness_by_country.png 中 ^[1]。

Details

About Dosu
This response is meant to be useful and save you time. It is not meant to be a precise solution, but rather a starting point for your own research.

Help me be more useful! Please leave a 👍 if this is helpful and 👎 if it is irrelevant.

To continue the conversation, mention @dosu.

[uniltone]

I need to save the image directly after returning response@dosu

[dosubot]

To save the image directly after the response is returned when using the pandas_query_engine, you can modify the _query method to include the code for saving the image. Here is an example of how you can do this:

def _query(self, query_bundle: QueryBundle) -> Response:
    """Answer a query."""
    context = self._get_table_context()

    pandas_response_str = self._llm.predict(
        self._pandas_prompt,
        df_str=context,
        query_str=query_bundle.query_str,
        instruction_str=self._instruction_str,
    )

    if self._verbose:
        print_text(f"> Pandas Instructions:\n" f"```\n{pandas_response_str}\n```\n")
    pandas_output = self._instruction_parser.parse(pandas_response_str)
    if self._verbose:
        print_text(f"> Pandas Output: {pandas_output}\n")

    # Execute the pandas code to generate the chart
    exec(pandas_output)

    # Save the chart image
    import matplotlib.pyplot as plt
    plt.savefig('chart.png')

    response_metadata = {
        "pandas_instruction_str": pandas_response_str,
        "raw_pandas_output": pandas_output,
    }
    if self._synthesize_response:
        response_str = str(
            self._llm.predict(
                self._response_synthesis_prompt,
                query_str=query_bundle.query_str,
                pandas_instructions=pandas_response_str,
                pandas_output=pandas_output,
            )
        )
    else:
        response_str = str(pandas_output)

    return Response(response=response_str, metadata=response_metadata)

In this code, after executing the pandas code to generate the chart, the plt.savefig('chart.png') function is called to save the chart image directly after the response is returned ^[1].

Details

About Dosu
This response is meant to be useful and save you time. It is not meant to be a precise solution, but rather a starting point for your own research.

Help me be more useful! Please leave a 👍 if this is helpful and 👎 if it is irrelevant.

To continue the conversation, mention @dosu.

[uniltone]

I tried your method, but it didn't work.
Keep reporting errors @dosu
Traceback (most recent call last):
File "E:\anaconda\Lib\site-packages\llama_index\experimental\query_engine\pandas\output_parser.py", line 54, in default_output_processor
output_str = str(safe_eval(module_end_str, {"np": np}, local_vars))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "E:\anaconda\Lib\site-packages\llama_index\experimental\exec_utils.py", line 159, in safe_eval
return eval(__source, _get_restricted_globals(__globals), __locals)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "", line 1, in
NameError: name 'p' is not defined

[dosubot]

The error "name 'p' is not defined" suggests that there is a missing import or a typo in the code being executed. Specifically, it seems like the code is trying to use a variable or function named p that hasn't been defined.

To resolve this, ensure that all necessary libraries are imported and used correctly. Here is an updated version of the code that includes the necessary imports and saves the generated chart:

import pandas as pd
import matplotlib.pyplot as plt
from llama_index.experimental.query_engine import PandasQueryEngine
from llama_index.llms.openai import OpenAI

df = pd.DataFrame(
    {
        "country": [
            "United States",
            "United Kingdom",
            "France",
            "Germany",
            "Italy",
            "Spain",
            "Canada",
            "Australia",
            "Japan",
            "China",
        ],
        "gdp": [
            21400000,
            2940000,
            2830000,
            3870000,
            2160000,
            1350000,
            1780000,
            1320000,
            516000,
            14000000,
        ],
        "happiness": [7.3, 7.2, 6.5, 7.0, 6.0, 6.3, 7.3, 7.3, 5.9, 5.0],
    }
)

llm = OpenAI()
query_engine = PandasQueryEngine(df=df, verbose=True)
response = query_engine.query(
    "Visualize bar chart of number of happiness of country.",
)

# Generate and save the bar chart
df.plot(kind='bar', x='country', y='happiness')
plt.xlabel('Country')
plt.ylabel('Happiness')
plt.title('Happiness by Country')
plt.savefig('happiness_by_country.png')  # Save the chart to a file
plt.show()

If you need to save the image directly after the response is returned within the _query method, ensure that the plotting library is correctly imported and used. Here is an example of how to modify the _query method:

def _query(self, query_bundle: QueryBundle) -> Response:
    """Answer a query."""
    context = self._get_table_context()

    pandas_response_str = self._llm.predict(
        self._pandas_prompt,
        df_str=context,
        query_str=query_bundle.query_str,
        instruction_str=self._instruction_str,
    )

    if self._verbose:
        print_text(f"> Pandas Instructions:\n" f"```\n{pandas_response_str}\n```\n")
    pandas_output = self._instruction_parser.parse(pandas_response_str)
    if self._verbose:
        print_text(f"> Pandas Output: {pandas_output}\n")

    # Execute the pandas code to generate the chart
    exec(pandas_output, {"plt": plt, "pd": pd})

    # Save the chart image
    plt.savefig('chart.png')

    response_metadata = {
        "pandas_instruction_str": pandas_response_str,
        "raw_pandas_output": pandas_output,
    }
    if self._synthesize_response:
        response_str = str(
            self._llm.predict(
                self._response_synthesis_prompt,
                query_str=query_bundle.query_str,
                pandas_instructions=pandas_response_str,
                pandas_output=pandas_output,
            )
        )
    else:
        response_str = str(pandas_output)

    return Response(response=response_str, metadata=response_metadata)

Make sure to include the necessary imports (import matplotlib.pyplot as plt and import pandas as pd) at the beginning of your script. This should resolve the "name 'p' is not defined" error and allow you to save the generated chart image ^[1][2].

To continue talking to Dosu, mention @dosu.

[tytung2020]

same issue here, have you solve it?
I think it is not related to matplotlib. I asked queries that are not related to plotting and it still returns this error:

Traceback (most recent call last):
  File "C:\Users\tytun\anaconda3\envs\pulse_ai\Lib\site-packages\llama_index\experimental\query_engine\pandas\output_parser.py", line 54, in default_output_processor
    output_str = str(safe_eval(module_end_str, global_vars, local_vars))
                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\tytun\anaconda3\envs\pulse_ai\Lib\site-packages\llama_index\experimental\exec_utils.py", line 159, in safe_eval
    return eval(__source, _get_restricted_globals(__globals), __locals)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "<string>", line 1, in <module>
NameError: name 'p' is not defined