如何像Excel中那样替换Python Panda中包含某些单词的单元格中的值

Question

我的数据是

性别

年龄
2年	男性
3个月	男性
2天	女性

使用替换函数。在您的情况下：

df.Age.replace({
"2 Year(s)": "2",
"3 Month(s)": "Below 1 year",
...
},
inplace=True
)

想明白了，我做到了，我从代码编辑器中复制粘贴了实际的代码

#split Patient Age and append back to master list
alldata[['Age', 'Unit']] = alldata['Patient Age'].str.split(' ', expand=True)
#Separate into subdata of Years, Months, Days and Hours
dfunit = alldata.groupby(['Unit'])
dfyears = dfunit.get_group('Year(s)')
dfmonths = dfunit.get_group('Month(s)')
dfdays = dfunit.get_group('Day(s)')
dfhours = dfunit.get_group('Hour(s)')

#Replace value of Mpnths, Days and Hours with 0
dfmonths['Age'] = dfmonths['Age'].str.replace('d', '0')
dfdays['Age'] = dfdays['Age'].str.replace('d', '0')
dfhours['Age'] = dfhours['Age'].str.replace('d', '0')

#Combine sublist back to master list
newdata = dfyears.append(dfmonths).append(dfdays).append(dfhours)
#Convert value in Age to int
newdata['Age'] = newdata['Age'].astype(int)
newdata['Age'].dtypes
#Separate Age into Age Group
bins = [0, 20, 30, 40, 50, 60, 70, 120]
labels = ['0-19', '20-29', '30-39', '40-49', '50-59', '60-69', '70+']
newdata['Agerange'] = pd.cut(newdata['Age'], bins, labels = labels,include_lowest = True)