Add column to a specific CSV row using Python pandas -


i want merge rows in csv files matching id given dictionary.

i have dictionary: l= {2.80215: [376570], 0.79577: [378053], 22667183: [269499]}

i have csv file.

                 b        c        d       2000-01-03 -0.59885 -0.18141 -0.68828 -0.77572 2000-01-04  0.83935  0.15993  0.95911 -1.12959 2000-01-05  2.80215 -0.10858 -1.62114 -0.20170 2000-01-06  0.71670 -0.26707  1.36029  1.74254 2000-01-07 -0.45749  0.22750  0.46291 -0.58431 2000-01-10 -0.78702  0.44006 -0.36881 -0.13884 2000-01-11  0.79577 -0.09198  0.14119  0.02668 2000-01-12 -0.32297  0.62332  1.93595  0.78024 2000-01-13  1.74683 -1.57738 -0.02134  0.11596 

the output should :

            b        c        d          e      f      2000-01-03 -0.59885 -0.18141 -0.68828 -0.77572    0 2000-01-04  0.83935  0.15993  0.95911 -1.12959    0 2000-01-05  2.80215 -0.10858 -1.62114 -0.20170    376570  2000-01-06  0.71670 -0.26707  1.36029  1.74254    0 2000-01-07 -0.45749  0.22750  0.46291 -0.58431    0 2000-01-10 -0.78702  0.44006 -0.36881 -0.13884    0 2000-01-11  0.79577 -0.09198  0.14119  0.02668    378053 2000-01-12 -0.32297  0.62332  1.93595  0.78024    0 2000-01-13  1.74683 -1.57738 -0.02134  0.11596    0  

i tried way:

import pandas data = panda.read_csv("thisfiel.csv")  data["f"] = data["b"].apply(lambda x: l[x]) 

but couldn't aimed results.

do this:

def getval(x):     try:         return l[x][0]      except keyerror:         return 0  data['f'] = data['b'].map(getval) 

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