What to do if "Unnamed: 0" is added in to_csv-> read_csv in pandas

The beginning of the matter

The incident happened when I simply performed CSV writing → reading in Python's pandas as follows.

import pandas as pd

#Define variable data and write to CSV file
data = pd.DataFrame({'name': ['Taro', 'Hanako', 'Jiro', 'Yuki'],
                      'Math': [80, 15, 90, 50],
                      'English': [80, 70, 50, 65],
                      'National language': [ 90, 60, 60,  60]})
print(data)
data.to_csv('a.csv')


#Read and output the exported CSV file
data = pd.read_csv('a.csv')
print(data)

When the above was executed, there was a difference in the output of each.

#First output result
name math English national language
0 Taro 80 80 90
1 Hanako 15 70 60
2 Jiro 90 50 60
3 Yuki 50 65 60


#Second output result
   Unnamed:0 name math English national language
0 0 Taro 80 80 90
1 1 Hanako 15 70 60
2 2 Jiro 90 50 60
3 3 Yuki 50 65 60

A mysterious column called ʻUnnamed: 0` has been added. Eliminate this.

What's happening?

In the above writing, the following CSV file was output.

,name,Math,English,National language
0,Taro,80,80,90
1,Hanako,15,70,60
2,Jiro,90,50,60
3,Yuki,50,65,60

An unexpected , has been added to the left of name on the first line. As a result, it seems that the first column is regarded as bearer.

approach

Either of the following can be used. You don't have to do both.

Supported by to_csv

It can be solved by specifying index as false as shown below.

data.to_csv('a.csv', index=False)

From the above, the following CSV file could be output.

name,Math,English,National language
0,Taro,80,80,90
1,Hanako,15,70,60
2,Jiro,90,50,60
3,Yuki,50,65,60

read_csv

Specify the index column as follows.

data = pd.read_csv('a.csv', index_col=0)

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