How to select rows based on dynamic column value?-CodePudding

First of all, I have following a following dataframe df_A

sector	SALES	EBIT	DPS
IT	xxxx	yyyy	zzz
ENERGY	xxxx	yyyy	zzz
FINANCE	xxxx	yyyy	zzz
CONSUMER	xxxx	yyyy	zzz

and another dataframe df_B

NAME	sector	SALES	EBIT	DPS
AAPL	IT	xxxx	yyyy	zzz
BP	ENERGY	xxxx	yyyy	zzz
TGT	CONSUMER	xxxx	yyyy	zzz
MSFT	IT	xxxx	yyyy	zzz
HSBC	FINANCE	xxxx	yyyy	zzz
GOOG	IT	xxxx	yyyy	zzz
WMT	CONSUMER	xxxx	yyyy	zzz
META	IT	xxxx	yyyy	zzz
CVX	ENERGY	xxxx	yyyy	zzz
JPM	FINANCE	xxxx	yyyy	zzz
MCD	CONSUMER	xxxx	yyyy	zzz

and so on

this is just an example, and I have a way bigger dataframe than this

what I want to do is to create new dataframes by distinguishing df_B by it's sectors;

where the newly created dataframes follow the order of df_A["sectors"]

and in the end merge them altogether, hopefully in horizontal format

so in the end I want my output to look like

NAME	sector	SALES	EBIT	DPS	NAME	sector	SALES	EBIT	DPS	NAME	sector	SALES	EBIT	DPS	NAME	sector	SALES	EBIT	DPS
AAPL	IT	xxxx	yyyy	zzz	BP	ENERGY	xxxx	yyyy	zzz	HSBC	FINANCE	xxxx	yyyy	zzz	WMT	CONSUMER	xxxx	yyyy	zzz
MSFT	IT	xxxx	yyyy	zzz	CVX	ENERGY	xxxx	yyyy	zzz	JPM	FINANCE	xxxx	yyyy	zzz	TGT	CONSUMER	xxxx	yyyy	zzz
GOOG	IT	xxxx	yyyy	zzz	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	MCD	CONSUMER	xxxx	yyyy	zzz
META	IT	xxxx	yyyy	zzz

if the horizontal format above doesn't work, vertical table will also be okay

I'm noob in python and I tried using for loops, dictionary, loc/iloc but somehow none of my codes is working properly...

Any help is deeply appreciated

CodePudding user response：

Create N dataframes, one for each sector, then concatenate them into a single one:

out = pd.concat([pd.DataFrame(df_B[df_B['sector'] == sector].to_dict('records'))
                    for sector in df_A['sector'].unique().tolist()], axis=1)
print(out)

# Output
   NAME sector SALES  EBIT  DPS NAME  sector SALES  EBIT  DPS  NAME   sector SALES  EBIT  DPS NAME    sector SALES  EBIT  DPS
0  AAPL     IT  xxxx  yyyy  zzz   BP  ENERGY  xxxx  yyyy  zzz  HSBC  FINANCE  xxxx  yyyy  zzz  TGT  CONSUMER  xxxx  yyyy  zzz
1  MSFT     IT  xxxx  yyyy  zzz  CVX  ENERGY  xxxx  yyyy  zzz   JPM  FINANCE  xxxx  yyyy  zzz  WMT  CONSUMER  xxxx  yyyy  zzz
2  GOOG     IT  xxxx  yyyy  zzz  NaN     NaN   NaN   NaN  NaN   NaN      NaN   NaN   NaN  NaN  MCD  CONSUMER  xxxx  yyyy  zzz
3  META     IT  xxxx  yyyy  zzz  NaN     NaN   NaN   NaN  NaN   NaN      NaN   NaN   NaN  NaN  NaN       NaN   NaN   NaN  NaN