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How to insert dictionaries as last lines in a Pandas DataFrame

I have the following framework:

import pandas as pd df = pd.DataFrame({'id':['a','b','c','d','e'], 'Sample1':[-14,-90,-90,-96,-91], 'Sample2':[-103,0,-110,-114,-114], 'Sample3':[1,2.3,3,5,6], }) df.set_index('id', inplace=True) df

It looks like this:

  Sample1 Sample2 Sample3 id a -14 -103 1.0 b -90 0 2.3 c -90 -110 3.0 d -96 -114 5.0 e -91 -114 6.0

I would like to insert the following dictionary

 mydict = { "Sample1": 0.023210000000000001, "Sample3": 0.039690000000000003, "Sample2": 0.05824 } mydict2 = { "Sample1": 0.7, "Sample3": 0.3, "Sample2": 0.8 }

as the last column with the names of the indices (rows) SRT and SRT2.

Yielding:

  Sample1 Sample2 Sample3 id a -14 -103 1.0 b -90 0 2.3 c -90 -110 3.0 d -96 -114 5.0 e -91 -114 6.0 SRT 0.23 0.39 0.05 SRT2 0.7 0.3 0.8

How can i achieve this?

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3 answers

You can use loc :

 df.loc['SRT'] = pd.Series(mydict) df.loc['SRT2'] = pd.Series(mydict2) print (df) Sample1 Sample2 Sample3 id a -14.00000 -103.00000 1.00000 b -90.00000 0.00000 2.30000 c -90.00000 -110.00000 3.00000 d -96.00000 -114.00000 5.00000 e -91.00000 -114.00000 6.00000 SRT 0.02321 0.05824 0.03969 SRT2 0.70000 0.80000 0.30000

Solution with concat :

 df1 = pd.DataFrame([mydict, mydict2], index=['SRT','SRT2']) print (df1) Sample1 Sample2 Sample3 SRT 0.02321 0.05824 0.03969 SRT2 0.70000 0.80000 0.30000 print (pd.concat([df,df1])) Sample1 Sample2 Sample3 a -14.00000 -103.00000 1.00000 b -90.00000 0.00000 2.30000 c -90.00000 -110.00000 3.00000 d -96.00000 -114.00000 5.00000 e -91.00000 -114.00000 6.00000 SRT 0.02321 0.05824 0.03969 SRT2 0.70000 0.80000 0.30000
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using append

 df.append(pd.Series(mydict, name='SRT')) Sample1 Sample2 Sample3 id a -14.00000 -103.00000 1.00000 b -90.00000 0.00000 2.30000 c -90.00000 -110.00000 3.00000 d -96.00000 -114.00000 5.00000 e -91.00000 -114.00000 6.00000 SRT 0.02321 0.05824 0.03969 
 df.append(pd.DataFrame.from_records([mydict, mydict2], ['SRT', 'SRT1'])) Sample1 Sample2 Sample3 a -14.00000 -103.00000 1.00000 b -90.00000 0.00000 2.30000 c -90.00000 -110.00000 3.00000 d -96.00000 -114.00000 5.00000 e -91.00000 -114.00000 6.00000 SRT 0.02321 0.05824 0.03969 SRT1 0.70000 0.80000 0.30000
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 a=df.append(pd.DataFrame(mydict,index=[0])) a=aT a=a.rename(columns={0:'SRT'}) a=aT
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Source: https://habr.com/ru/post/1262404/

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