df = pd.read_csv('ccf_offline_stage1_train.csv')
print(df['Distance'])
df['distance'] = df['Distance'].fillna(-1).astype(int)
print(df['distance'])

#導(dǎo)包
import pandas as pd
import numpy as np
from numpy import nan as NaN

df1=pd.DataFrame([[1,2,3],[NaN,NaN,2],[NaN,NaN,NaN],[8,8,NaN]])
df1

#一、不指定method參數(shù)
 
#1.用常數(shù)填充
print (df1.fillna(100))
print ("-----------------------")
print (df1)

#2.用字典填充
df1.fillna({0:10,1:20,2:30})

#二、指定inplace參數(shù)
 
print (df1.fillna(0,inplace=True))
print ("-------------------------")
print (df1)

#三、指定method參數(shù)
 
df2 = pd.DataFrame(np.random.randint(0,10,(5,5)))
df2.iloc[1:4,3] = NaN
df2.iloc[2:4,4] = NaN
df2

#1.method = 'ffill'/'pad'：用前一個(gè)非缺失值去填充該缺失值
 
df2.fillna(method='ffill')

#2.method = 'bflii'/'backfill'：用下一個(gè)非缺失值填充該缺失值
 
df2.fillna(method='bfill')

#四、指定limit參數(shù)
 
#用下一個(gè)非缺失值填充該缺失值
#只填充2個(gè)
 
df2.fillna(method='bfill', limit=2)

#五、指定axis參數(shù)
 
df2.fillna(method="ffill", limit=1, axis=1)