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)remove duplicates python
mylist = ["a", "b", "a", "c", "c"]
mylist = list(dict.fromkeys(mylist))python remove duplicates
word = input().split()
for i in word:
if word.count(i) > 1:
word.remove(i)pandas remove repeated index
idx = pd.Index(['lama', 'cow', 'lama', 'beetle', 'lama', 'hippo'])
idx.drop_duplicates(keep='first')
Index(['lama', 'cow', 'beetle', 'hippo'], dtype='object')
idx.drop_duplicates(keep='last')
Index(['cow', 'beetle','lamb', 'hippo'], dtype='object')
idx.drop_duplicates(keep='False')
Index(['cow', 'beetle','hippo'], dtype='object')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|
# +---+------+-----+Copyright © 2021 Codeinu
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