st.write (df) gives problem when df is a pivot table

Summary

Showing a dataframe gives an error ArrowInvalid: (‘Could not convert All with type str: tried to convert to int’, ‘Conversion failed for column MM with type object’)

Steps to reproduce

Code snippet:

import pandas as pd
import streamlit as st


def get_data():
    url = "https://raw.githubusercontent.com/rcsmit/streamlit_scripts/main/input/garminactivities_new.csv"
    df = pd.read_csv(url, delimiter=';')
    df["Datum"] = pd.to_datetime(df["Datum"], format="%d-%m-%Y")
    df = df.sort_values(by=['Datum'])
    df["YYYY"] = df["Datum"].dt.year
    df["MM"] = df["Datum"].dt.month
    df["DD"] = df["Datum"].dt.day
    df["count"] = 1
    df = df[df["Activiteittype"] == "Hardlopen"].copy(deep=False)
    df = df[["Datum","Titel", "Afstand","Tijd", "gem_snelh", "count", "MM", "YYYY"]]
    return df

def find_nr_activities_per_month_per_year(df):
    # Aantal activiteiten per maand (per jaar)
    df_pivot = df.pivot_table(index='MM', columns='YYYY', values='count',  aggfunc='sum', fill_value=0, margins = True)
    st.write(df_pivot) #gives error
    print (df_pivot) # not a problem

def main():
    df = get_data().copy(deep=False)

    find_nr_activities_per_month_per_year(df)


if __name__ == "__main__":
    main()

Dtypes of the dataframe:

Datum        datetime64[ns]
Titel                object
Afstand             float64
Tijd                 object
gem_snelh           float64
count                 int64
MM                    int64
YYYY                  int64

Expected behavior: Showing the dataframe. print(df) doesn’t throw an error

Actual behavior:

Is this a regression?

I don’t know

Debug info

• Streamlit version: 0.85
• Python version: 3.8
• Using Conda? PipEnv? PyEnv? Pex? Nothing of this
• OS version: Windows
• Browser version: Chrome, latest

Additional information

n/a

[vdonato]

Hi @rcsmit, sorry for the delayed reply – I missed your last reply until now. The error seems to be related / probably has the same root cause, so I don’t think there’s a need to open a second issue.

[rcsmit]

One thing that could be done here would be to cast the integers in the MM to all have type str.

Thanks a lot for your reply and help.

For those who arrive here after googling

df["MM"] = df["MM"].astype(str).str.zfill(2)

does the job ( .str.zfill(2) is to prevent the 1 10 11 12 3 4 etc order)