我已经看到了这个问题,但它并没有为我工作,我相信我犯了一个大错,但请告诉我我做错了什么,我想要价值观" Street",& #34; LandContour"等等将被替换为" pave"到1等等。
python pandas replacing strings in dataframe with numbers
这是我的代码,直到现在:
import numpy as np
import pandas as pd
df=pd.read_csv('train.csv') # getting file
df.fillna(-99999, inplace=True)
#df.replace("Street", 0, True) didn't work
# mapping={'Street':1,'LotShape':2,'LandContour':3,'Utilities':4,'SaleCondition':5}
# df.replace('Street', 0) # didn't work
# df.replace({'Street': mapping, 'LotShape': mapping,
# 'LandContour': mapping, 'Utilities': mapping,
# 'SaleCondition': mapping})
# didn't work ^
df.head()
我尝试了df['Street'].replace("pave",0,inplace=True)
和许多其他事情,但都没有效果。甚至df.replace中给出的参数的单个值也不会被替换。我的df工作正常,它打印头部和特定的颜色,df.fillna
也工作正常。任何帮助都会很棒。
编辑:所有未注释的行都在工作,我希望未注释的行能够正常工作。
示例输出为: -
Id MSSubClass MSZoning LotFrontage LotArea Street Alley LotShape \
0 1 60 RL 65.0 8450 Pave -99999 Reg
1 2 20 RL 80.0 9600 Pave -99999 Reg
2 3 60 RL 68.0 11250 Pave -99999 IR1
3 4 70 RL 60.0 9550 Pave -99999 IR1
4 5 60 RL 84.0 14260 Pave -99999 IR1
LandContour Utilities ... PoolArea PoolQC Fence MiscFeature \
0 Lvl AllPub ... 0 -99999 -99999 -99999
1 Lvl AllPub ... 0 -99999 -99999 -99999
2 Lvl AllPub ... 0 -99999 -99999 -99999
3 Lvl AllPub ... 0 -99999 -99999 -99999
4 Lvl AllPub ... 0 -99999 -99999 -99999
MiscVal MoSold YrSold SaleType SaleCondition SalePrice
0 0 2 2008 WD Normal 208500
1 0 5 2007 WD Normal 181500
2 0 9 2008 WD Normal 223500
3 0 2 2006 WD Abnorml 140000
4 0 12 2008 WD Normal 250000
我也尝试过: -
mapping={'Pave':1,'Lvl':2,'AllPub':3,'Reg':4,'Normal':5,'Abnormal':0,'IR1':6}
#df.replace('Street',0)
df.replace({'Street': mapping, 'LotShape': mapping,
'LandContour': mapping, 'Utilities': mapping, 'SaleCondition': mapping})
但那也没有用^
答案 0 :(得分:3)
尝试:
df = pd.read_csv('train.csv') # reset
df.fillna(-99999, inplace=True) # refill
df['Street'].replace('Pave', 0, inplace=True) # replace
您之前的方法存在的问题是,它们不会使用正确的搜索值将替换应用于正确的列。也要注意资本化。