Answers for "pandas dataframe drop duplicates based on one column"

5

python: remove duplicate in a specific column

df = df.drop_duplicates(subset=['Column1', 'Column2'], keep='first')
Posted by: Guest on July-22-2020
3

drop duplicates pandas first column

import pandas as pd 
  
# making data frame from csv file 
data = pd.read_csv("employees.csv") 
  
# sorting by first name 
data.sort_values("First Name", inplace = True) 
  
# dropping ALL duplicte values 
data.drop_duplicates(subset ="First Name",keep = False, inplace = True) 
  
# displaying data 
print(data)
Posted by: Guest on June-28-2020
2

remove duplicates based on two columns in dataframe

df.drop_duplicates(['A','B'],keep= 'last')
Posted by: Guest on August-13-2020
0

Return a new DataFrame with duplicate rows removed

# Return a new DataFrame with duplicate rows removed

from pyspark.sql import Row
df = sc.parallelize([
  Row(name='Alice', age=5, height=80),
  Row(name='Alice', age=5, height=80),
  Row(name='Alice', age=10, height=80)]).toDF()
df.dropDuplicates().show()
# +---+------+-----+
# |age|height| name|
# +---+------+-----+
# |  5|    80|Alice|
# | 10|    80|Alice|
# +---+------+-----+

df.dropDuplicates(['name', 'height']).show()
# +---+------+-----+
# |age|height| name|
# +---+------+-----+
# |  5|    80|Alice|
# +---+------+-----+
Posted by: Guest on April-08-2020

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