知识要点
依据索引获取数据：
列索引：df_obj[‘label’]
不连续列索引：df_obj[ [‘label1’, ‘label2’] ]
行索引，loc[ ]，iloc[ ]
Inplace 参数：
Pandas中的很多操作都有参数inplace，如 drop()，replace() …
默认 inplace=False，表示将操作后的结果进行返回，对原始数据不会产生影响
inplace=True，没有返回值，在原始数据上进行操作，对原始数据会产生影响
第五节 DataFrame的索引操作
In [1]:
import pandas as pd
import numpy as np
In [3]:
构建DataFrame
country1 = pd.Series({'Name':'中国',
'Language':'Chinese',
'Area':'9.597M km2',
'Happiness Rank': 79})
country2 = pd.Series({'Name':'美国',
'Language':'USA',
'Area':'9.83M km2',
'Happiness Rank': 14})
country3 = pd.Series({'Name':'澳大利亚',
'Language':'Austria',
'Area':'7.692M km2',
'Happiness Rank': 9})
df = pd.DataFrame([country1,country2,country3],index=['CH','US','AU'])
In [4]:
Out[4]:
NameLanguageAreaHappiness RankCH中国Chinese9.597M km279US美国USA9.83M km214AU澳大利亚Austria7.692M km29
In [5]:
df['Area']
Out[5]:
CH 9.597M km2
US 9.83M km2
AU 7.692M km2
Name: Area, dtype: object
In [7]:
df[['Area','Name']]
Out[7]:
AreaNameCH9.597M km2中国US9.83M km2美国AU7.692M km2澳大利亚
In [10]:
type(df.loc['CH'])
Out[10]:
pandas.core.series.Series
In [9]:
df.iloc[1]
Out[9]:
Name 美国
Language USA
Area 9.83M km2
Happiness Rank 14
Name: US, dtype: object
In [11]:
先行后列
print(df.loc['CH']['Area'])
print(df.iloc[0]['Area'])
9.597M km2
9.597M km2
In [12]:
先列后行
print(df['Area']['CH'])
print(df['Area'].loc['CH'])
print(df['Area'].iloc[0])
9.597M km2
9.597M km2
9.597M km2
In [13]:
Out[13]:
NameLanguageAreaHappiness RankCH中国Chinese9.597M km279US美国USA9.83M km214AU澳大利亚Austria7.692M km29
In [14]:
删除Area列
df.drop('Area',axis=1)
Out[14]:
NameLanguageHappiness RankCH中国Chinese79US美国USA14AU澳大利亚Austria9
In [15]:
df没有影响
Out[15]:
NameLanguageAreaHappiness RankCH中国Chinese9.597M km279US美国USA9.83M km214AU澳大利亚Austria7.692M km29
In [16]:
写法1：默认inplace=False,返回操作后的结果
df2 = df.drop('Area',axis=1)
df2
Out[16]:
NameLanguageHappiness RankCH中国Chinese79US美国USA14AU澳大利亚Austria9
In [17]:
写法2:inplace=True,在员数据上产生影响，返回None
df.drop('Area',axis=1,inplace=True)
Out[17]:
NameLanguageHappiness RankCH中国Chinese79US美国USA14AU澳大利亚Austria9
In [ ]:
Original: https://blog.csdn.net/u011868279/article/details/114990004
Author: 梦想家DBA
Title: 数据分析工具Pandas基础–DataFrame的索引操作
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