1
我試圖用np.nan
值替換我的數據框中由'...'反映的缺失值。 我也想更新一些舊的值,但我的方法似乎不工作。使用Numpy和Pandas替換缺失值和更新數據幀中的舊值
這裏是我的代碼:
import numpy as np
import pandas as pd
def func():
energy=pd.ExcelFile('Energy Indicators.xls').parse('Energy')
energy=energy.iloc[16:][['Environmental Indicators: Energy','Unnamed: 3','Unnamed: 4','Unnamed: 5']].copy()
energy.columns=['Country', 'Energy Supply', 'Energy Supply per Capita', '% Renewable']
o="..."
n=np.NaN
# Trying to replace missing values with np.nan values
energy[energy['Energy Supply']==o]=n
energy['Energy Supply']=energy['Energy Supply']*1000000
# Here, I want to replace old values by new ones ==> Same problem
old=["Republic of Korea","United States of America","United Kingdom of "
+"Great Britain and Northern Ireland","China, Hong "
+"Kong Special Administrative Region"]
new=["South Korea","United States","United Kingdom","Hong Kong"]
for i in range(0,4):
energy[energy['Country']==old[i],'Country']=new[i]
return energy
這裏是.xls
文件我的工作:https://drive.google.com/file/d/0B80lepon1RrYeDRNQVFWYVVENHM/view?usp=sharing
我覺得應該是'能量= energy.replace( '...',np.nan,正則表達式= FALSE)' – MaxU
@MaxU正則表達式默認爲false,這意味着有什麼事不對勁列值(可能導致空白),所以我決定去正則表達式。也會加入你的! –
'energy = energy.replace('...',np.nan)'效果很好 – sali333