Python 如何更改分类列值?
在我的数据框架中,我有一列“国家”,我试图将该列的值改为“发达国家”和“发展中国家”。我的数据框如下所示:Python 如何更改分类列值?,python,pandas,data-science,data-cleaning,Python,Pandas,Data Science,Data Cleaning,在我的数据框架中,我有一列“国家”,我试图将该列的值改为“发达国家”和“发展中国家”。我的数据框如下所示: countries age gender 1 India 21 Male 2 China 22 Female 3 USA 23 Male 4 UK 25 Male 我有以下两个阵列: developed = ['USA','UK'] developing = ['India', 'China'] 我想将数组转换为以下数据帧
countries age gender
1 India 21 Male
2 China 22 Female
3 USA 23 Male
4 UK 25 Male
我有以下两个阵列:
developed = ['USA','UK']
developing = ['India', 'China']
我想将数组转换为以下数据帧:
countries age gender
1 developing 21 Male
2 developing 22 Female
3 developed 23 Male
4 developed 25 Male
我尝试了以下代码,但出现了“SettingWithCopyWarning”错误:
df[df['countries'].isin(developed)]['countries'] = 'developed'
我尝试了以下代码,但出现了“SettingWithCopyWarning”错误,我的jupyter笔记本被挂起:
for i, x in enumerate(df['countries']):
if x in developed:
df['countries'][i] = 'developed'
是否有其他方法可以更改列类别???使用:
您还可以使用:
使用:
您还可以使用:
您可以尝试实现replace函数,它不会给出错误
Updated_DataSet1 = data_set.replace("India", "Developing")
Updated_DataSet2 = Updated_DataSet1.replace("China","Developing")
您可以尝试实现replace函数,它不会给出错误
Updated_DataSet1 = data_set.replace("India", "Developing")
Updated_DataSet2 = Updated_DataSet1.replace("China","Developing")
Updated_DataSet1 = data_set.replace("India", "Developing")
Updated_DataSet2 = Updated_DataSet1.replace("China","Developing")