pandas資料索引 loc iloc和ix

1、loc

通過行標籤索引行資料

（1）、loc[『d』]：獲取第』d』行資料

import pandas as pd  

data = [[1,2,3],[4,5,6]] 
index = [『d』,'e'] 
columns=['a','b','c'] 
df = pd.dataframe(data=data, index=index, columns=columns) 
print(df.loc['e'])

a    4

b 5
c 6
name: 1, dtype: int64

獲取第『d』行及之後的多行資料

import pandas as pd  

data = [[1,2,3],[4,5,6]] 
index = ['d','e'] 
columns=['a','b','c'] 
df = pd.dataframe(data=data, index=index, columns=columns) 
print(df.loc['d':])

a  b  c

d 1 2 3
e 4 5 6

loc['d',['b']]索引第『d』行第『b』列

import pandas as pd  

data = [[1,2,3],[4,5,6]] 
index = ['d','e'] 
columns=['a','b','c'] 
df = pd.dataframe(data=data, index=index, columns=columns) 
print(df.loc['d',['b']])

b    2

name: d, dtype: int64

2、iloc

通過行號獲取行資料

(1)、iloc[1]獲取第1行資料

import pandas as pd  

data = [[1,2,3],[4,5,6]] 
index = ['d','e'] 
columns=['a','b','c'] 
df = pd.dataframe(data=data, index=index, columns=columns) 
print(df.iloc[1])

a    4

b 5
c 6
name: e, dtype: int64

獲取第0行及之後的多行資料

import pandas as pd  

data = [[1,2,3],[4,5,6]] 
index = ['d','e'] 
columns=['a','b','c'] 
df = pd.dataframe(data=data, index=index, columns=columns) 
print(df.iloc[0:])

a  b  c

d 1 2 3
e 4 5 6

獲取第1列資料

import pandas as pd  

data = [[1,2,3],[4,5,6]] 
index = ['d','e'] 
columns=['a','b','c'] 
df = pd.dataframe(data=data, index=index, columns=columns) 
print(df.iloc[:,[1]])

b

d 2
e 5

前兩種的混合索引，python3已經不使用這種索引方式。

pandas資料選擇（索引）

import pandas as pd import numpy as npdates pd.date range 20180101 periods 6 df pd.dataframe np.arange 24 reshape 6,4 index dates,columns a b c d prin...

pandas資料新索引 reindex

dataframe.reindex labels none,index none,columns none,axis none,method none,copy true,level none,fill value nan,limit none,tolerance none 常用關鍵引數 metho...

pandas資料的索引操作

coding utf 8 series索引 行索引 import pandas as pd import numpy as np ser obj pd.series range 5 index a b c d e print ser obj 行索引獲單個值 print ser obj b ser o...