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.drop duplicates()

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Pleasant Peccary answered on March 4, 2022 Popularity 9/10 Helpfulness 3/10

answer .drop duplicates()

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.drop duplicates()

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df = pd.DataFrame({"Date": ["2022", "2022", "2021", "2021", "2020", "2020"], "Time": ["20:00", "20:00", "20:00", "21:00", "22:00", "22:00"]})
df.drop_duplicates()

#output
#	Date	Time
#	2022	20:00
#	2021	20:00
#	2021	21:00
#	2020	22:00

Popularity 9/10 Helpfulness 3/10 Language python

Source: Grepper

Tags: python

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Contributed on Sep 02 2022

Pleasant Peccary

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delete the entire row while remove duplicates with python'

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result_df = df.drop_duplicates(subset=['Column1', 'Column2'], keep='first')
print(result_df)

Popularity 10/10 Helpfulness 6/10 Language python

Source: stackoverflow.com

Tags: python py

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Contributed on Mar 04 2022

Doubtful Dugong

0 Answers Avg Quality 2/10

pandas drop duplicates

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borrar duplicados pandas

# Below are quick example
# keep first duplicate row
df2 = df.drop_duplicates()

# Using DataFrame.drop_duplicates() to keep first duplicate row
df2 = df.drop_duplicates(keep='first')

# keep last duplicate row
df2 = df.drop_duplicates( keep='last')

# Remove all duplicate rows 
df2 = df.drop_duplicates(keep=False)

# Delete duplicate rows based on specific columns 
df2 = df.drop_duplicates(subset=["Courses", "Fee"], keep=False)

# Drop duplicate rows in place
df.drop_duplicates(inplace=True)

# Using DataFrame.apply() and lambda function 
df2 = df.apply(lambda x: x.astype(str).str.lower()).drop_duplicates(subset=['Courses', 'Fee'], keep='first')

Popularity 9/10 Helpfulness 4/10 Language c

Source: sparkbyexamples.com

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Contributed on Feb 16 2023

malloc

0 Answers Avg Quality 2/10

drop_duplicates

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df.drop_duplicates()

Popularity 9/10 Helpfulness 2/10 Language python

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Tags: python py

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Contributed on Dec 07 2022

Georgiy Kantsedal

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python drop duplicates order by

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import pandas as pd

mydictionary = {'id': ['11X', '11X', '22X', '33A'],
                'grade': [68, 74, 77, 78],
                'checkdate': ["2019-12-26", "2019-12-27", "2019-12-26", "2019-12-25"]}

df = pd.DataFrame(mydictionary)

df['checkdate'] = pd.to_datetime(df['checkdate'])
df2 = df.sort_values(by=['checkdate']).drop_duplicates('id', keep='last')
print(df2)

Popularity 4/10 Helpfulness 1/10 Language python

Source: stackoverflow.com

Tags: python

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Contributed on Sep 02 2024

peamdev

0 Answers Avg Quality 2/10

.drop duplicates()

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