start index at 1 for Pandas DataFrame

Question

I need the index to start at 1 rather than 0 when writing a Pandas DataFrame to CSV.

Here's an example:

In [1]: import pandas as pd

In [2]: result = pd.DataFrame({'Count': [83, 19, 20]})

In [3]: result.to_csv('result.csv', index_label='Event_id')                               

Which produces the following output:

In [4]: !cat result.csv
Event_id,Count
0,83
1,19
2,20

But my desired output is this:

In [5]: !cat result2.csv
Event_id,Count
1,83
2,19
3,20

I realize that this could be done by adding a sequence of integers shifted by 1 as a column to my data frame, but I'm new to Pandas and I'm wondering if a cleaner way exists.

Solution 1

Index is an object, and default index starts from 0:

>>> result.index
Int64Index([0, 1, 2], dtype=int64)

You can shift this index by 1 with

>>> result.index += 1 
>>> result.index
Int64Index([1, 2, 3], dtype=int64)

Solution 2

Just set the index before writing to CSV.

df.index = np.arange(1, len(df))

And then write it normally.

Solution 3

source: In Python pandas, start row index from 1 instead of zero without creating additional column

Working example:

import pandas as pdas
dframe = pdas.read_csv(open(input_file))
dframe.index = dframe.index + 1

Solution 4

Another way in one line:

df.shift()[1:]

Solution 5

This worked for me

 df.index = np.arange(1, len(df)+1)

View more solutions

Comments

[yourstruly]

somehow it changes index name - so proper order with naming is: df.index+=1;df.index.name='name'

[Dung]

where np is import like so: import numpy as np

[Natesh bhat]

it should be df.index = arange( 1, len(df) + 1)

[Armali]

This drops the last row.

[santhosh_dj]

efficient way : df.index = range(1, df.shape[0] + 1)