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Removing values from Series in Pandas

schedule Aug 10, 2023
Last updated
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Removing values using integer indices

To remove values using integer indices, use the drop(~) method like so:

import pandas as pd
s = pd.Series([3,5,4,5])
s.drop(index=2)
0 3
1 5
3 5
dtype: int64

Here, a new Series is returned and so the original s is kept intact. To directly modify s, set inplace=True.

Removing values using index labels

To remove values using index labels, use the drop(~) method:

s = pd.Series([3,5,4,5], index=["a","b","c","d"])
s.drop("a")
b 5
c 4
d 5
dtype: int64

Removing occurrences of values

To remove all occurrences of the value 5:

s = pd.Series([3,5,4,5])
s.loc[s != 5]
0 3
2 4
dtype: int64

To explain, we first fetch a boolean mask where True indicates a value that is not 5:

s != 5
0 True
1 False
2 True
3 False
dtype: bool

We then pass this mask into the loc property to fetch the entries that correspond to True in the mask.

Removing values using slicing

To remove the values from integer index 1 (inclusive) to 3 (exclusive):

s = pd.Series([3,5,4,5])
s.drop(s.index[1:3])
0 3
3 5
dtype: int64
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Published by Isshin Inada
Edited by 0 others
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