Explanation of the difference between. loc and. iloc and. at and. iat in pandas

Display index and implicit index

import pandas as pd
df = pd.DataFrame({' Name ':[' Zhang 3',' Li 4',' Wang 5'],' Achievement ':[85,59,76]})

Pass in a colon ':', which indicates all rows or columns

Display index:. loc, the first parameter is index slice, and the second parameter is columns column name

df.loc[2] #index For 2 Records of , This is the king 5 The results. 
df.loc[:,' Name '] # No. 1 1 The parameters are colons, which indicate all rows. Here is the column record of Filter Name. 

Implicit index:. iloc (integer_location), only integers can be passed in.

df.iloc[:2,:] # Zhang 3 And Lee 4 The achievement of , Slicing with list 1 Sample, colon closes left and opens right. 
df.iloc[:,' Achievement '] # If you enter Chinese, you will report an error here, and you can only use integers. 

You can also navigate to an element using at

Grammar rule: df. at [index, columns]

df.at[1,' Achievement '] # Using index tags, Lee 4 The achievement of 
df.iat[1,1] # Similar to iloc Accessing an element using an implicit index 

Supplement: pandas quickly locates all rows with a certain value in a 1 column, loc, at, = = comparison

As shown below:

goodDiskName2016

from datetime import datetime
from time import time

Position equal columns with direct square brackets

start = time()
for disk in goodDiskName2016[:100]:
   　 ____ST4000DM000_2016_good_feature27[ST4000DM000_2016_good_feature27.serial_number==disk][features27[0]]
time()-start

Time consumed

82.93997383117676

Direct loc positioning is equal

start = time()
for disk in goodDiskName2016[:100]:  ____ST4000DM000_2016_good_feature27.loc[ST4000DM000_2016_good_feature27.serial_number==disk][features27[0]]
time()-start

Time elapsed:

82.4887466430664

First set this 1 column to index, and then find it through loc

df.loc[2] #index For 2 Records of , This is the king 5 The results. 
df.loc[:,' Name '] # No. 1 1 The parameters are colons, which indicate all rows. Here is the column record of Filter Name. 

0

df.loc[2] #index For 2 Records of , This is the king 5 The results. 
df.loc[:,' Name '] # No. 1 1 The parameters are colons, which indicate all rows. Here is the column record of Filter Name. 

1

Time elapsed:

df.loc[2] #index For 2 Records of , This is the king 5 The results. 
df.loc[:,' Name '] # No. 1 1 The parameters are colons, which indicate all rows. Here is the column record of Filter Name. 

2

Position with at after setting to index

start = time()
for disk in goodDiskName2016[:100]:
 b.at[disk,features27[0]]
time()-start

Time elapsed:

df.loc[2] #index For 2 Records of , This is the king 5 The results. 
df.loc[:,' Name '] # No. 1 1 The parameters are colons, which indicate all rows. Here is the column record of Filter Name. 

4