如何从行值设置列名?
How to set name of columns from rows values?
如何设置如附图所示的列名?
我加入了多个 dfs,但为列生成了非代表性名称。
dfs=
[data_3,data_4,data_5,data_6,data_7,data_8,data_9,data_11,data_12,data_13,data_14]
df_final = reduce(lambda left,right: pd.merge(left,right,on='date'), dfs)
df_final.set_index('date')
Screenshot
如评论中所述,您可以根据枚举器重命名数据框中的列:
new_dfs = [i.rename(columns =
dict(zip(i.columns.difference(['date']),i.columns.difference(['date']) + f"_dfno_{e}")))
for e,i in enumerate(dfs,3)]
然后在 reduce
下试试:
df_final = reduce(lambda left,right: pd.merge(left,right,on='date'), new_dfs )
df_final.set_index('date')
如何设置如附图所示的列名? 我加入了多个 dfs,但为列生成了非代表性名称。
dfs=
[data_3,data_4,data_5,data_6,data_7,data_8,data_9,data_11,data_12,data_13,data_14]
df_final = reduce(lambda left,right: pd.merge(left,right,on='date'), dfs)
df_final.set_index('date')
Screenshot
如评论中所述,您可以根据枚举器重命名数据框中的列:
new_dfs = [i.rename(columns =
dict(zip(i.columns.difference(['date']),i.columns.difference(['date']) + f"_dfno_{e}")))
for e,i in enumerate(dfs,3)]
然后在 reduce
下试试:
df_final = reduce(lambda left,right: pd.merge(left,right,on='date'), new_dfs )
df_final.set_index('date')