Concatenate a blank df to a list of dataframes-CodePudding

I have the following data:

import pandas as pd
import numpy as np
from numpy import rec, nan
    
df1=pd.DataFrame.from_records(rec.array([(202001L, 2020L, 'apples', 'CA', 100L),(202002L, 2020L, 'apples', 'CA', 150L),(202001L, 2020L, 'apples', 'USA', 400L),(202002L, 2020L, 'apples', 'USA', 675L),        ], 
 dtype=[('yyyymm', '<i8'), ('year', '<i8'), ('prod', 'O'), ('country', 'O'), ('rev', '<i8')]))
    
df2=df1[['yyyymm','prod','country','rev']].sort_values(['yyyymm','prod','country'])
df2['yyyymm'] = df2['yyyymm'].astype(str)
        
twenty_eight_days=['02']
thirty_days=['09','04','06','11']
thirty_one_days=['01','03','05','07','08','10','12']
        
df2['mth_nbr']=df2['yyyymm'].str[-2:]
df2['year_nbr']=df2['yyyymm'].str[:4]
df2.loc[df2['mth_nbr'].isin(twenty_eight_days), 'last_day']= '28'
df2.loc[df2['mth_nbr'].isin(thirty_days), 'last_day'] = '30'
df2.loc[df2['mth_nbr'].isin(thirty_one_days), 'last_day'] = '31'
        df2['date']=pd.to_datetime(df2['year_nbr'] df2['mth_nbr'] df2['last_day'])
df2.set_index(df2['date'],inplace=True)
df2.drop(['yyyymm','mth_nbr','year_nbr','last_day','date'], axis=1, inplace=True)  
df2

I break out df2 by country: df2_CA and df2_USA. I want to attach a blank dataframe called df_forecast to each of df2_CA & df2_USA so I can forecast:

# 1. : Create 2 new dfs by country: df2_CA and df2_USA:
#######################################################
for x in df2['country'].unique():
    locals()['df2_'   x ] = df2[(df2['country'] == x ) ]   

    
#2. Create a forecasting dataframe:
###################################
index = pd.date_range('2020-03-30', periods=3, freq='M')
columns = ['prod','country','rev']
df_forecast = pd.DataFrame(index=index, columns=columns)


#3. Append df_forecast to each of df2_CA, df2_USA:
#################################################

df_list=[df2_CA, df2_USA]

for x in df_list:
    x=pd.concat([x, df_forecast]) 
    x['prod'].fillna(method='ffill',inplace=True)     
    x['country'].fillna(method='ffill',inplace=True)
    x.loc['2020-03':'2020-05', 'rev'] = 200

However if I look at df2_CA, df_forecast is not appending:

When I code df2_CA (and df2_USA) separately I get the desired result:

What is wrong with the for-loop in step 3 above?

CodePudding user response：

Have you made sure all dataframes have the same columns?

CodePudding user response：

Because your dataframe is blank (ie just header no rows) the concatenation has nothing to add to the existing dataframe.

You could add a first row with NaN values for instance and then edit these values later on.