Python---根据列表中包含值的字典,将数据框列名拆分为多个列名 df=pd.DataFrame( {'animals':'deer','devices':'phone','movies':'inseption'}, 索引=[1] ) col_map=OrderedDict( { “动物”:[“水生动物”、“陆地动物”], “设备”:[“技术”], “电影”:[“电影院”] } ) df2=df.rename(列=列映射) 输出
期望输出Python---根据列表中包含值的字典,将数据框列名拆分为多个列名 df=pd.DataFrame( {'animals':'deer','devices':'phone','movies':'inseption'}, 索引=[1] ) col_map=OrderedDict( { “动物”:[“水生动物”、“陆地动物”], “设备”:[“技术”], “电影”:[“电影院”] } ) df2=df.rename(列=列映射) 输出,python,python-3.x,pandas,list,dictionary,Python,Python 3.x,Pandas,List,Dictionary,期望输出 data = [['beer', 10], ['whiskey', 40], ['vodka', 50]] df = pd.DataFrame(data,columns=['a','b']) print('Input df') display(df) col_map = {'a':['liquor'],'b':['percentage','%']} col_map_fil = {} for k,v in col_map.items(): if len(v) > 1:
data = [['beer', 10], ['whiskey', 40], ['vodka', 50]]
df = pd.DataFrame(data,columns=['a','b'])
print('Input df')
display(df)
col_map = {'a':['liquor'],'b':['percentage','%']}
col_map_fil = {}
for k,v in col_map.items():
if len(v) > 1:
for i in v:
df[i] = df[k]
df.pop(k)
else:
col_map_fil.update({k:v[0]})
df = df.rename(columns=col_map_fil)
print('Output df')
display(df)