I am trying the merge the datetime series with a repository data while grouping by name and summing the values.

File1.csv Timeseries,Name,count
07/03/2015 06:00:00,Paris,100
07/03/2015 06:00:00,Paris,600
07/03/2015 06:00:00,Paris,700
07/03/2015 06:00:00,London,200
07/03/2015 06:00:00,London,100
07/03/2015 06:00:00,London,500
07/03/2015 06:00:00,Dublin,300
07/03/2015 06:00:00,Dublin,400
07/03/2015 06:00:00,Dublin,400

Output

Master_file.csv (append mode)Name,Timeseries(n-1)Timeseries(n)#put the datetime series as header and put       Paris,300,1400      #Sum of all the values with same NameLondon,200,800Dublin,400,1100Program import pandas as pd 
import numpy as npdf = pd.read_csv('/home/lat_lon1.csv')
df1 = pd.read_csv('/home/lat_lon_master.csv')gp = df.groupby('Name')['date timeseries'].sum().reset_index() 
df1.merge(gp, on='Name')

I am having trouble in changing the date time column to header and putting the correct values under. Those Names not found can be given NAN and replaced in next iterations.

Please check the python pandas Data Frame documentation Click here Here is the code you are looking at.

Output

Timeseries Name count07/03/2015 06:00:00 Dublin 110007/03/2015 06:00:00 London 80007/03/2015 06:00:00 Paris 1400

   #!/bin/pythonimport pandas as pdimport numpy as npdf=pd.read_csv('/home/saiharsh/Documents/Crowd Street/Transition_Data/Telecom_7.csv') #Please enter the file Locationgp=df.groupby('Name').sum().reset_index()flag=0for i in gp['Name']:if flag==1:time=df['Timeseries'][df['Name']==i]time=time.tail(1)frames=[time1,time]time1=pd.concat(frames)else:time1=df['Timeseries'][df['Name']==i]time1=time1.tail(1)flag=1time1=time1.reset_index(drop=True)result=pd.concat([time1,gp],axis=1,join='inner')result=result.to_csv(index=False)print result

Please feel free to reply if any problem.