replace
df['消费性别倾向'] = df['消费性别倾向'].replace(2,'女')
df['消费性别倾向'] = df['消费性别倾向'].replace('2','女')
df['消费性别倾向'] = df['消费性别倾向'].replace(['1','2','3','4','5'],'女')
df['消费性别倾向'] = df['消费性别倾向'].replace(['6','7','8','9'],'男')传入表示映射关系的字典作为参数
food = {'<=100':'1','100-500':'2','500-1000':'3','1000-3000':'4','>3000':'5'}
df['工作日消费指数'] = df['工作日消费金额'].replace(food)map
food = {'<=100':'1','100-500':'2','500-1000':'3','1000-3000':'4','>3000':'5'}
df['工作日消费指数'] = df['工作日消费金额'].map(food)注：如果map中需要包含映射列的所有取值的映射关系。