Remove some columns

[menator01]

Can use the usecols

import pandas as pd

df = pd.read_csv('test.csv', usecols=[0,1,2,4,6])

print(df)

Output

Output:
  Age      Sex    BMI      Region   Charges
0   21     male  25.75   northeast   3279.87
1   37   female  25.74   southeast  21454.49
2   18     male  30.03   southeast   1720.35
3   37     male  30.68   northeast   6801.44
4   58     male  32.01   southeast  11946.63
5   46     male  26.62   southeast   7742.11
6   25     male  31.19   northeast  21736.33

---

Using tabulate for display

# Do the imports
import pandas as pd
from tabulate import tabulate 

# Read the csv file with selected columns
df = pd.read_csv('test.csv', usecols=[0,1,2,4,6])

# Create new csv file
df.to_csv('newcsv.csv', index=False)

# Read new csv file
new_df = pd.read_csv('newcsv.csv')

# Using tabulate to format display output
new_df = tabulate(new_df, headers=list(new_df), showindex=False, tablefmt='pretty')

# Print new_df
print(new_df)

Output

Output:
+-----+--------+-------+-----------+----------+
| Age |  Sex   |  BMI  |  Region   | Charges  |
+-----+--------+-------+-----------+----------+
| 21  |  male  | 25.75 | northeast | 3279.87  |
| 37  | female | 25.74 | southeast | 21454.49 |
| 18  |  male  | 30.03 | southeast | 1720.35  |
| 37  |  male  | 30.68 | northeast | 6801.44  |
| 58  |  male  | 32.01 | southeast | 11946.63 |
| 46  |  male  | 26.62 | southeast | 7742.11  |
| 25  |  male  | 31.19 | northeast | 21736.33 |
+-----+--------+-------+-----------+----------+