BUG: very minor error I can't understand but was easily fixed.

[markingt0n]

Pandas version checks

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• I have confirmed this bug exists on the latest version of pandas.

• I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

import pandas as pd

df = [*things*]

df = df[df['price'] > 0]

Issue Description

TypeError: '>' not supported between instances of 'str' and 'int'

Expected Behavior

Where it happened and why is the only question. Obviously, you could assume I was trying to use a maths operator on a string, but that shouldn't be what happened.

I ran code containing the above in google colabs, worked fine. it was only in vscode the error came up. The data was via an api call, the same data, some 20 minutes after it was 1st called.

I fixed it with this, df['price'] = pd.to_numeric(df['price'], errors='coerce') , easy, no problems.

The code was copy pasted, 1:1 no changes. I imagine colab may use an older version? Anyway, very minor issue but a bit odd. For whatever reason different versions have interpreted the exact same data as a different type.

Installed Versions

Latest stable version as of 11/05/2023 on vscode
Whatever Colab are using.

[KianShah]

It is hard to tell what the issue is without knowing what data was being passed to pandas. In my experience, pandas will sometimes convert columns to the 'object' type, so you have to coerce the column data type to integer. Maybe try running df['price'].dtypes and seeing what that outputs

[topper-123]

Can you provide a more precise example. Otherwise we can't verify the issue you're reporting.

[markingt0n]

from dash import Dash, html, dash_table, dcc, callback, Output, Input, State
import pandas as pd
import plotly.express as px
import os
import requests
import pandas as pd
from datetime import datetime, timedelta
import webbrowser
import dash_bootstrap_components as dbc
import plotly.graph_objects as go 

# check if data is fresh, if not get a fresh version

url = f'https://steamspy.com/api.php?request=top100owned'

def get_data():
    # Check if the CSV file from the last 24 hours exists
    
    if os.path.exists(csv_file):
        file_modified_time = os.path.getmtime(csv_file)
        file_modified_datetime = datetime.fromtimestamp(file_modified_time)
        time_difference = datetime.now() - file_modified_datetime

        if time_difference < timedelta(hours=24):
            # Load the existing CSV file
            df = pd.read_csv(csv_file)
            print('i read the file')
            

    else:
        response = requests.get(url)

        if response.status_code == 200:
            data = response.json()


            # Convert dictionary to a list of dictionaries
            data_list = [v for _, v in data.items()]

            # Create DataFrame from the list of dictionaries
            df = pd.DataFrame(data_list)

             print('I had to get the data')

            df.to_csv(csv_file, index=False)
        else:
            print('Error: API request failed.')
    return df

df.head(30)


print('i read the file')

## data cleaning
df = get_data()
#df['price'] = pd.to_numeric(df['price'], errors='coerce') # fix commented out
df = df[df['price'] > 0]`
df.head(25)

There's the segment that caused the error. In this instance it read the file correctly from local storage. So there's no issues on the API end.

[topper-123]

That is still not reproducible and there's too much going on in the example and doesn't show what error to expect, nor what result would be the correct one.

See minimally reproducible example on SO or search for the term for how to makes small code examples for bug reports.

[mroeschke]

Closing until we can get a more reproducible example