Drop rows and reset_index in a dataframe

Question

I was wondering why reset_index() has no effect in the following piece of code.

data = [0,10,20,30,40,50]
df = pd.DataFrame(data, columns=['Numbers'])
df.drop(df.index[2:4], inplace=True)
df.reset_index()
df

   Numbers
0        0
1       10
4       40
5       50

UPDATE:

If I use df.reset_index(inplace=True), I see a new column which is not desired.

   index  Numbers
0      0        0
1      1       10
2      4       40
3      5       50

score 3 · Accepted Answer · answered Feb 15 '23 at 09:24

3

Because reset_index() has inplace=False as default, so you need to do reset_index(inplace=True). Docs

answered Feb 15 '23 at 09:24

Minh-Long Luu

2,393
1
17
39

1

You then have to add `drop` as well: `.reset_index(inplace=True, drop=True)` – Minh-Long Luu Feb 15 '23 at 09:57

score 0 · Answer 2 · answered Feb 15 '23 at 09:35

Please try this code

import pandas as pd

# create a sample DataFrame
df = pd.DataFrame({'column_name': [1, 2, 0, 4, 0, 6]})

# drop rows where column 'column_name' has value of 0
df = df[df['column_name'] != 0]

# reset the index of the resulting DataFrame
df = df.reset_index(drop=True)

print(df)

Drop rows and reset_index in a dataframe

2 Answers2