How to drop rows in Pandas DataFrame by index labels? - GeeksforGeeks
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How to drop rows in Pandas DataFrame by index labels?
Last Updated: 02-07-2020Pandas provide data analysts a way to delete and filter data frame using .drop()
method. Rows can be removed using index label or column name using this method.
Syntax:
DataFrame.drop(labels=None, axis=0, index=None, columns=None, level=None, inplace=False, errors=’raise’)Parameters:
labels: String or list of strings referring row or column name.
axis: int or string value, 0 ‘index’ for Rows and 1 ‘columns’ for Columns.
index or columns: Single label or list. index or columns are an alternative to axis and cannot be used together.
level: Used to specify level in case data frame is having multiple level index.
inplace: Makes changes in original Data Frame if True.
errors: Ignores error if any value from the list doesn’t exists and drops rest of the values when errors = ‘ignore’Return type: Dataframe with dropped values
Now, Let’s create a sample dataframe
filter_none
edit
close
play_arrow
link
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code
# import pandas library
import
pandas as pd
# dictionary with list object in values
details
=
{
'Name'
: [
'Ankit'
,
'Aishwarya'
,
'Shaurya'
,
'Shivangi'
],
'Age'
: [
23
,
21
,
22
,
21
],
'University'
: [
'BHU'
,
'JNU'
,
'DU'
,
'BHU'
],
}
# creating a Dataframe object
df
=
pd.DataFrame(details,columns
=
[
'Name'
,
'Age'
,
'University'
],
index
=
[
'a'
,
'b'
,
'c'
,
'd'
])
df
Output:
Example #1: Delete a single Row in DataFrame by Row Index Label
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close
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link
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code
# import pandas library
import
pandas as pd
# dictionary with list object in values
details
=
{
'Name'
: [
'Ankit'
,
'Aishwarya'
,
'Shaurya'
,
'Shivangi'
],
'Age'
: [
23
,
21
,
22
,
21
],
'University'
: [
'BHU'
,
'JNU'
,
'DU'
,
'BHU'
],
}
# creating a Dataframe object
df
=
pd.DataFrame(details, columns
=
[
'Name'
,
'Age'
,
'University'
],
index
=
[
'a'
,
'b'
,
'c'
,
'd'
])
# return a new dataframe by dropping a
# row 'c' from dataframe
update_df
=
df.drop(
'c'
)
update_df
Output :
Example #2: Delete Multiple Rows in DataFrame by Index Labels
filter_none
edit
close
play_arrow
link
brightness_4
code
# import pandas library
import
pandas as pd
# dictionary with list object in values
details
=
{
'Name'
: [
'Ankit'
,
'Aishwarya'
,
'Shaurya'
,
'Shivangi'
],
'Age'
: [
23
,
21
,
22
,
21
],
'University'
: [
'BHU'
,
'JNU'
,
'DU'
,
'BHU'
],
}
# creating a Dataframe object
df
=
pd.DataFrame(details, columns
=
[
'Name'
,
'Age'
,
'University'
],
index
=
[
'a'
,
'b'
,
'c'
,
'd'
])
# return a new dataframe by dropping a row
# 'b' & 'c' from dataframe
update_df
=
df.drop([
'b'
,
'c'
])
update_df
Output :
Example #3: Delete a Multiple Rows by Index Position in DataFrame
filter_none
edit
close
play_arrow
link
brightness_4
code
# import pandas library
import
pandas as pd
# dictionary with list object in values
details
=
{
'Name'
: [
'Ankit'
,
'Aishwarya'
,
'Shaurya'
,
'Shivangi'
],
'Age'
: [
23
,
21
,
22
,
21
],
'University'
: [
'BHU'
,
'JNU'
,
'DU'
,
'BHU'
],
}
# creating a Dataframe object
df
=
pd.DataFrame(details, columns
=
[
'Name'
,
'Age'
,
'University'
],
index
=
[
'a'
,
'b'
,
'c'
,
'd'
])
# return a new dataframe by dropping a row
# 'b' & 'c' from dataframe using their
# respective index position
update_df
=
df.drop([df.index[
1
], df.index[
2
]])
update_df
Output :
Example #4: Delete rows from dataFrame in Place
filter_none
edit
close
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link
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code
# import pandas library
import
pandas as pd
# dictionary with list object in values
details
=
{
'Name'
: [
'Ankit'
,
'Aishwarya'
,
'Shaurya'
,
'Shivangi'
],
'Age'
: [
23
,
21
,
22
,
21
],
'University'
: [
'BHU'
,
'JNU'
,
'DU'
,
'BHU'
],
}
# creating a Dataframe object
df
=
pd.DataFrame(details, columns
=
[
'Name'
,
'Age'
,
'University'
],
index
=
[
'a'
,
'b'
,
'c'
,
'd'
])
# droppping a row 'c' & 'd' from actual dataframe
df.drop([
'c'
,
'd'
], inplace
=
True
)
df
Output :
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