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Terminal_Output.txt
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python .\src\agent_for_code_excecution\main.py
# Agent: Senior Data Analyst Specialist
## Task: Conduct a comprehensive analysis of the provided dataset to identify the top 10 counties with the highest violent crime rates. The dataset is located at C:\Users\Sushant.Dhumak\OneDrive - Bentley Systems, Inc\Desktop\AI_Learning\crewai\agent_for_code_excecution\src\agent_for_code_excecution/County_Health_Rankings.csv and contains the following columns:
- State: The state where the county is located - County: The name of the county - Year span: The time period over which the crime data was collected - Measure name: The type of crime (in this case, Violent crime rate) - Raw value: The actual crime rate value
Your task is to create and execute a Python code to extract the top 10 counties with the highest violent crime rates, along with their corresponding raw values, year spans, and county names. Ensure that the results are sorted in descending order based on the raw values.
Requirement already satisfied: pandas in c:\users\sushant.dhumak\onedrive - bentley systems, inc\desktop\ai_learning\crewai\.venv\lib\site-packages (2.2.3)
Requirement already satisfied: numpy>=1.26.0 in c:\users\sushant.dhumak\onedrive - bentley systems, inc\desktop\ai_learning\crewai\.venv\lib\site-packages (from pandas) (2.2.1)
Requirement already satisfied: python-dateutil>=2.8.2 in c:\users\sushant.dhumak\onedrive - bentley systems, inc\desktop\ai_learning\crewai\.venv\lib\site-packages (from pandas) (2.9.0.post0)
Requirement already satisfied: pytz>=2020.1 in c:\users\sushant.dhumak\onedrive - bentley systems, inc\desktop\ai_learning\crewai\.venv\lib\site-packages (from pandas) (2024.2)
Requirement already satisfied: tzdata>=2022.7 in c:\users\sushant.dhumak\onedrive - bentley systems, inc\desktop\ai_learning\crewai\.venv\lib\site-packages (from pandas) (2024.2)
Requirement already satisfied: six>=1.5 in c:\users\sushant.dhumak\onedrive - bentley systems, inc\desktop\ai_learning\crewai\.venv\lib\site-packages (from python-dateutil>=2.8.2->pandas) (1.17.0)
State County Year span Raw value
12854 NM Guadalupe County 2005-2007 3265.306122
12855 NM Guadalupe County 2006-2008 2843.888665
11356 MO St. Louis city 2005-2007 2368.883881
11355 MO St. Louis city 2004-2006 2323.382557
535 AK Dillingham Census Area 2006-2008 2295.782168
11357 MO St. Louis city 2006-2008 2265.143444
11354 MO St. Louis city 2003-2005 2222.822703
532 AK Dillingham Census Area 2003-2005 2160.371107
11358 MO St. Louis city 2007-2009 2136.637194
536 AK Dillingham Census Area 2007-2009 2116.543871
🖇 AgentOps: Could not record event - no sessions detected. Create a session by calling agentops.start_session()
# Agent: Senior Data Analyst Specialist
## Thought: I need to read the dataset from the specified file path and filter the data to extract the counties with the highest violent crime rates. I will then sort the data based on the raw values in descending order and select the top 10 counties along with their corresponding details.
## Using tool: Code Interpreter
## Tool Input:
"{\"code\": \"import pandas as pd\\n\\n# Load the dataset\\ndf = pd.read_csv(r'C:\\\\Users\\\\Sushant.Dhumak\\\\OneDrive - Bentley Systems, Inc\\\\Desktop\\\\AI_Learning\\\\crewai\\\\agent_for_code_excecution\\\\src\\\\agent_for_code_excecution/County_Health_Rankings.csv')\\n\\n# Filter for violent crime rates\\ndf_violent_crime = df[(df['Measure name'] == 'Violent crime rate')]\\n\\n# Sort the counties by raw value in descending order and select top 10\\ntop_10_violent_crime = df_violent_crime[['State', 'County', 'Year span', 'Raw value']]\\n\\ntop_10_violent_crime = top_10_violent_crime.sort_values(by='Raw value', ascending=False).head(10)\\n\\n# Print the final result\\nprint(top_10_violent_crime)\", \"libraries_used\": [\"pandas\"]}"
## Tool Output:
No result variable found.
Requirement already satisfied: pandas in c:\users\sushant.dhumak\onedrive - bentley systems, inc\desktop\ai_learning\crewai\.venv\lib\site-packages (2.2.3)
Requirement already satisfied: numpy>=1.26.0 in c:\users\sushant.dhumak\onedrive - bentley systems, inc\desktop\ai_learning\crewai\.venv\lib\site-packages (from pandas) (2.2.1)
Requirement already satisfied: python-dateutil>=2.8.2 in c:\users\sushant.dhumak\onedrive - bentley systems, inc\desktop\ai_learning\crewai\.venv\lib\site-packages (from pandas) (2.9.0.post0)
Requirement already satisfied: pytz>=2020.1 in c:\users\sushant.dhumak\onedrive - bentley systems, inc\desktop\ai_learning\crewai\.venv\lib\site-packages (from pandas) (2024.2)
Requirement already satisfied: tzdata>=2022.7 in c:\users\sushant.dhumak\onedrive - bentley systems, inc\desktop\ai_learning\crewai\.venv\lib\site-packages (from pandas) (2024.2)
Requirement already satisfied: six>=1.5 in c:\users\sushant.dhumak\onedrive - bentley systems, inc\desktop\ai_learning\crewai\.venv\lib\site-packages (from python-dateutil>=2.8.2->pandas) (1.17.0)
State County Year span Raw value
12854 NM Guadalupe County 2005-2007 3265.306122
12855 NM Guadalupe County 2006-2008 2843.888665
11356 MO St. Louis city 2005-2007 2368.883881
11355 MO St. Louis city 2004-2006 2323.382557
535 AK Dillingham Census Area 2006-2008 2295.782168
11357 MO St. Louis city 2006-2008 2265.143444
11354 MO St. Louis city 2003-2005 2222.822703
532 AK Dillingham Census Area 2003-2005 2160.371107
11358 MO St. Louis city 2007-2009 2136.637194
536 AK Dillingham Census Area 2007-2009 2116.543871
# Agent: Senior Data Analyst Specialist
## Using tool: Code Interpreter
## Tool Input:
"{\"code\": \"import pandas as pd\\n\\n# Load the dataset\\ndf = pd.read_csv(r'C:\\\\Users\\\\Sushant.Dhumak\\\\OneDrive - Bentley Systems, Inc\\\\Desktop\\\\AI_Learning\\\\crewai\\\\agent_for_code_excecution\\\\src\\\\agent_for_code_excecution/County_Health_Rankings.csv')\\n\\n# Filter for violent crime rates\\ndf_violent_crime = df[df['Measure name'] == 'Violent crime rate']\\n\\n# Sort the counties by raw value in descending order and select top 10\\ntop_10_violent_crime = df_violent_crime[['State', 'County', 'Year span', 'Raw value']].sort_values(by='Raw value', ascending=False).head(10)\\n\\n# Print the final result\\nprint(top_10_violent_crime)\", \"libraries_used\": [\"pandas\"]}"
## Tool Output:
No result variable found.
Requirement already satisfied: pandas in c:\users\sushant.dhumak\onedrive - bentley systems, inc\desktop\ai_learning\crewai\.venv\lib\site-packages (2.2.3)
Requirement already satisfied: numpy>=1.26.0 in c:\users\sushant.dhumak\onedrive - bentley systems, inc\desktop\ai_learning\crewai\.venv\lib\site-packages (from pandas) (2.2.1)
Requirement already satisfied: python-dateutil>=2.8.2 in c:\users\sushant.dhumak\onedrive - bentley systems, inc\desktop\ai_learning\crewai\.venv\lib\site-packages (from pandas) (2.9.0.post0)
Requirement already satisfied: pytz>=2020.1 in c:\users\sushant.dhumak\onedrive - bentley systems, inc\desktop\ai_learning\crewai\.venv\lib\site-packages (from pandas) (2024.2)
Requirement already satisfied: tzdata>=2022.7 in c:\users\sushant.dhumak\onedrive - bentley systems, inc\desktop\ai_learning\crewai\.venv\lib\site-packages (from pandas) (2024.2)
Requirement already satisfied: six>=1.5 in c:\users\sushant.dhumak\onedrive - bentley systems, inc\desktop\ai_learning\crewai\.venv\lib\site-packages (from python-dateutil>=2.8.2->pandas) (1.17.0)
State County Year span Raw value
12854 NM Guadalupe County 2005-2007 3265.306122
12855 NM Guadalupe County 2006-2008 2843.888665
11356 MO St. Louis city 2005-2007 2368.883881
11355 MO St. Louis city 2004-2006 2323.382557
535 AK Dillingham Census Area 2006-2008 2295.782168
11357 MO St. Louis city 2006-2008 2265.143444
11354 MO St. Louis city 2003-2005 2222.822703
532 AK Dillingham Census Area 2003-2005 2160.371107
11358 MO St. Louis city 2007-2009 2136.637194
536 AK Dillingham Census Area 2007-2009 2116.543871
# Agent: Senior Data Analyst Specialist
## Using tool: Code Interpreter
## Tool Input:
"{\"code\": \"import pandas as pd\\n\\n# Load the dataset\\ndf = pd.read_csv(r'C:\\\\Users\\\\Sushant.Dhumak\\\\OneDrive - Bentley Systems, Inc\\\\Desktop\\\\AI_Learning\\\\crewai\\\\agent_for_code_excecution\\\\src\\\\agent_for_code_excecution/County_Health_Rankings.csv')\\n\\n# Filter for violent crime rates\\ndf_violent_crime = df[df['Measure name'] == 'Violent crime rate']\\n\\n# Sort the counties by raw value in descending order and select top 10\\ntop_10_violent_crime = df_violent_crime[['State', 'County', 'Year span', 'Raw value']].sort_values(by='Raw value', ascending=False).head(10)\\n\\n# Prepare the result for output\\nresult = top_10_violent_crime\\nprint(result)\", \"libraries_used\": [\"pandas\"]}"
## Tool Output:
State County Year span Raw value
12854 NM Guadalupe County 2005-2007 3265.306122
12855 NM Guadalupe County 2006-2008 2843.888665
11356 MO St. Louis city 2005-2007 2368.883881
11355 MO St. Louis city 2004-2006 2323.382557
535 AK Dillingham Census Area 2006-2008 2295.782168
11357 MO St. Louis city 2006-2008 2265.143444
11354 MO St. Louis city 2003-2005 2222.822703
532 AK Dillingham Census Area 2003-2005 2160.371107
11358 MO St. Louis city 2007-2009 2136.637194
536 AK Dillingham Census Area 2007-2009 2116.543871
You ONLY have access to the following tools, and should NEVER make up tools that are not listed here:
Tool Name: Code Interpreter
Tool Arguments: {'code': {'description': 'Python3 code used to be interpreted in the Docker container. ALWAYS PRINT the final result and the output of the code', 'type': 'str'}, 'libraries_used': {'description': 'List of libraries used in the code with proper installing names separated by commas. Example: numpy,pandas,beautifulsoup4', 'type': 'list[str]'}}
Tool Description: Interprets Python3 code strings with a final print statement.
Use the following format:
Thought: you should always think about what to do
Action: the action to take, only one name of [Code Interpreter], just the name, exactly as it's written.
Action Input: the input to the action, just a simple python dictionary, enclosed in curly braces, using " to wrap keys and values.
Observation: the result of the action
Once all necessary information is gathered:
Thought: I now know the final answer
Final Answer: the final answer to the original input question
Requirement already satisfied: pandas in c:\users\sushant.dhumak\onedrive - bentley systems, inc\desktop\ai_learning\crewai\.venv\lib\site-packages (2.2.3)
Requirement already satisfied: numpy>=1.26.0 in c:\users\sushant.dhumak\onedrive - bentley systems, inc\desktop\ai_learning\crewai\.venv\lib\site-packages (from pandas) (2.2.1)
Requirement already satisfied: python-dateutil>=2.8.2 in c:\users\sushant.dhumak\onedrive - bentley systems, inc\desktop\ai_learning\crewai\.venv\lib\site-packages (from pandas) (2.9.0.post0)
Requirement already satisfied: pytz>=2020.1 in c:\users\sushant.dhumak\onedrive - bentley systems, inc\desktop\ai_learning\crewai\.venv\lib\site-packages (from pandas) (2024.2)
Requirement already satisfied: tzdata>=2022.7 in c:\users\sushant.dhumak\onedrive - bentley systems, inc\desktop\ai_learning\crewai\.venv\lib\site-packages (from pandas) (2024.2)
Requirement already satisfied: six>=1.5 in c:\users\sushant.dhumak\onedrive - bentley systems, inc\desktop\ai_learning\crewai\.venv\lib\site-packages (from python-dateutil>=2.8.2->pandas) (1.17.0)
State County Year span Raw value
NM Guadalupe County 2005-2007 3265.306122
NM Guadalupe County 2006-2008 2843.888665
MO St. Louis city 2005-2007 2368.883881
MO St. Louis city 2004-2006 2323.382557
AK Dillingham Census Area 2006-2008 2295.782168
MO St. Louis city 2006-2008 2265.143444
MO St. Louis city 2003-2005 2222.822703
AK Dillingham Census Area 2003-2005 2160.371107
MO St. Louis city 2007-2009 2136.637194
AK Dillingham Census Area 2007-2009 2116.543871
# Agent: Senior Data Analyst Specialist
## Thought: Thought: The Python code executed successfully, and I've obtained the top 10 counties with the highest violent crime rates along with their corresponding values. Now, I'll structure the final output to present the results clearly.
## Using tool: Code Interpreter
## Tool Input:
"{\"code\": \"import pandas as pd\\n\\n# Load the dataset\\ndf = pd.read_csv(r'C:\\\\Users\\\\Sushant.Dhumak\\\\OneDrive - Bentley Systems, Inc\\\\Desktop\\\\AI_Learning\\\\crewai\\\\agent_for_code_excecution\\\\src\\\\agent_for_code_excecution/County_Health_Rankings.csv')\\n\\n# Filter for violent crime rates\\ndf_violent_crime = df[df['Measure name'] == 'Violent crime rate']\\n\\n# Sort the counties by raw value in descending order and select top 10\\ntop_10_violent_crime = df_violent_crime[['State', 'County', 'Year span', 'Raw value']].sort_values(by='Raw value', ascending=False).head(10)\\n\\n# Prepare the result for final output\\nresult = top_10_violent_crime.to_string(index=False)\\nprint(result)\", \"libraries_used\": [\"pandas\"]}"
## Tool Output:
State County Year span Raw value
NM Guadalupe County 2005-2007 3265.306122
NM Guadalupe County 2006-2008 2843.888665
MO St. Louis city 2005-2007 2368.883881
MO St. Louis city 2004-2006 2323.382557
AK Dillingham Census Area 2006-2008 2295.782168
MO St. Louis city 2006-2008 2265.143444
MO St. Louis city 2003-2005 2222.822703
AK Dillingham Census Area 2003-2005 2160.371107
MO St. Louis city 2007-2009 2136.637194
AK Dillingham Census Area 2007-2009 2116.543871
# Agent: Senior Data Analyst Specialist
## Final Answer:
```
State County Year span Raw value
NM Guadalupe County 2005-2007 3265.306122
NM Guadalupe County 2006-2008 2843.888665
MO St. Louis city 2005-2007 2368.883881
MO St. Louis city 2004-2006 2323.382557
AK Dillingham Census Area 2006-2008 2295.782168
MO St. Louis city 2006-2008 2265.143444
MO St. Louis city 2003-2005 2222.822703
AK Dillingham Census Area 2003-2005 2160.371107
MO St. Louis city 2007-2009 2136.637194
AK Dillingham Census Area 2007-2009 2116.543871
```
This table summarizes the top 10 counties with the highest violent crime rates, including their state, county name, year span, and raw value.
```
State County Year span Raw value
NM Guadalupe County 2005-2007 3265.306122
NM Guadalupe County 2006-2008 2843.888665
MO St. Louis city 2005-2007 2368.883881
MO St. Louis city 2004-2006 2323.382557
AK Dillingham Census Area 2006-2008 2295.782168
MO St. Louis city 2006-2008 2265.143444
MO St. Louis city 2003-2005 2222.822703
AK Dillingham Census Area 2003-2005 2160.371107
MO St. Louis city 2007-2009 2136.637194
AK Dillingham Census Area 2007-2009 2116.543871
```
This table summarizes the top 10 counties with the highest violent crime rates, including their state, county name, year span, and raw value.