import pandas as pd
import numpy as np

df=pd.DataFrame(np.random.randint(0,150,size=(150,3)),
                columns=['math','python','english']
                )
print(df)
print(df.python)
print(df["math"])
print(df[['math']])
print(df[['math','python']])

import pandas as pd
import numpy as np

df=pd.DataFrame(np.random.randint(0,100,size=(10,3)),
                index=list('ABCDEFGHIG'),
                columns=['math','python','english']
                )
print(df.loc['A'])#篩選出標(biāo)簽A這一行
print(df.loc[['A']])#將A這一行返回成一個新的DataFrame
print(df.loc[['A','B']])#將AB兩行返回成DataFrame
print(df.loc[['A','B'],['math','python']])#左邊為標(biāo)簽，右邊為字段，即將AB兩行的math、python兩列返回
print(df.loc['A':'F',['math','python']])#采用分區(qū)方法，將A到F行的此兩列返回
print(df.loc[:,['math','python']])#單獨的‘:'表示所有行
print(df.loc['B'::2])#從B開始隔一個取一個

import pandas as pd
import numpy as np

df=pd.DataFrame(np.random.randint(0,151,size=(2000,3)),
                columns=['math','python','english']
                )
cond1=df.python>99#其返回值為一個bool類型的series，需要變量進行接受
print(cond1)
df1=df[cond1]
print(df1[['python']])#將cond1作為篩選條件，這里為了只看其中一列，用一個新的dataframe

print(df[df>50])#對df中的所有元素進行判定，其false項會換成NaN

print(df[df.python.isin([108])])#使用isin方法查找python分?jǐn)?shù)為108，中括號里也可以為數(shù)組

df2=df.query('python>135 and math>120 and english > 100')
print(df2)