drop_duplicates()
1、不定义任何参数，完全删除重复的行数据
2、去除重复的几列行数据
import pandas as pd
df = pd.DataFrame({
'brand': ['Yum Yum', 'Yum Yum', 'Indomie', 'Indomie', 'Indomie'],
'style': ['cup', 'cup', 'cup', 'pack', 'pack'],
'rating': [4, 4, 3.5, 15, 5]})
print("---------------------原始数据：")
print(df)
print("------------------------df.drop_duplicates()")
print(df.drop_duplicates())
print("------------------------删除在brand列中重复的数据行")
print(df.drop_duplicates(subset='brand'))
print("------------------------重复行保留第一次出现的行，删除其他行")
print(df.drop_duplicates(keep="first"))
print("----------------------inplace 布尔值，默认为False，是否直接在原数据上删除重复项或删除重复项后返回副本")
print("-----------------inplace=False 删除重复项后返回副本")
print(df.drop_duplicates(inplace=False))
print("-------------df1")
print(df)
print("-----------------inplace=True 直接在原数据上删除重复项")
print(df.drop_duplicates(inplace=True))
print("-------------df2")
print(df)
`python
brand style rating
0 Yum Yum cup 4.0
2 Indomie cup 3.5
3 Indomie pack 15.0
4 Indomie pack 5.0
brand style rating
0 Yum Yum cup 4.0
2 Indomie cup 3.5
3 Indomie pack 15.0
4 Indomie pack 5.0
brand style rating
0 Yum Yum cup 4.0
2 Indomie cup 3.5
3 Indomie pack 15.0
4 Indomie pack 5.0
None
subset: 指定重复数据所在的列。column label or sequence of labels, optional
Only consider certain columns for identifying duplicates, by
default use all of the columns.
keep: {‘first’, ‘last’, False}, default ‘first’
Determines which duplicates (if any) to keep.
-
first: 除了第一次出现以外，删除重复项。Drop duplicates except for the first occurrence. -
last: 除了第一次出现以外，删除重复项。Drop duplicates except for the last occurrence. -
False: 删除所有重复项。Drop all duplicates.
inplace:True:直接在原始数据删除，False：不直接在原始数据删除，并生成一个副本。bool, default False
Whether to drop duplicates in place or to return a copy.
ignore_index: bool, default False
If True, the resulting axis will be labeled 0, 1, …, n – 1.
.. versionadded:: 1.0.0
Returns
DataFrame.value_counts: Count unique combinations of columns.
示例：
Original: https://blog.csdn.net/c_lanxiaofang/article/details/125880941
Author: 懒笑翻
Title: df.drop_duplicates() 详解+用法
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