I have a data set with mixed index values, int and str, which df.to_csv reads as an object.
If I try to slice the rows this does not work, I get a TypeError.
I know I can work around it by changing the index dtype, but I would like to understand why this happens, or if there's a different way of slicing these mixed dtype indices?
I've created the following test case:
import os
import pandas as pd
import numpy as np
#all str index
df1 = pd.DataFrame({'Col': [0, 20, 30, 10]}, index=['a', 'b','c','d'])
#all int index
df2 = pd.DataFrame({'Col': [0, 20, 30, 10]}, index=[1, 2, 3, 4])
#all str index with numbers
df3 = pd.DataFrame({'Col': [0, 20, 30, 10]}, index=['a', 'b', '3', '4'])
#mixed str/int
df4 = pd.DataFrame({'Col': [0, 20, 30, 10]}, index=['a', 'b', 3, 4 ])
df1.loc['b':'d']
Col
b 20
c 30
d 10
df2.loc[2:4]
Col
2 20
3 30
4 10
df3.loc['b':'4']
Col
b 20
3 30
4 10
df4.loc['b':4]
TypeError
df4.index = df4.index.map(str)
df4.loc['b':'4']
Col
b 20
3 30
4 10
Why does the slice not work for df4? Can you 'fix it' within the slice? Is changing the dtype of the index the only option?