Index error - columns vs non-column

[snippsat]

The error is clear and the problem lay in df Dataframe.
When do index=df["Date"] means that the Dataframe most have column named Date.
To show a example.

import pandas as pd

data = {
    "Name": ["Tom", "nick", "krish", "jack"],
    "Date": [20, 21, 19, 18],
}

df = pd.DataFrame(data)

>>> df
    Name  Date
0    Tom    20
1   nick    21
2  krish    19
3   jack    18

>>> df['Date']
0    20
1    21
2    19
3    18
Name: Date, dtype: int64

>>> df.columns
Index(['Name', 'Date'], dtype='object')

If eg put a space in Date string it will fail with your error.

>>> df['Date']
Traceback (most recent call last):
.....  
KeyError: 'Date'

# Date most be the exact name and a column in df
>>> df.columns
Index(['Name', 'Date '], dtype='object')