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Python: append dictionary to pandas data frame row

Time:11-29

I have a dictionary of following form:

{'2018': 21.6, '2019': 29.0, '2020': 134.8}

and a pandas dataframe of the following form

Index Column1 Column2
Index1 Name1 URL1
Index2 Name2 URL2
Index3 Name3 URL3

my aim now is to append the dictionary to a fixed row, say the row with Index2. The result dataframe then should be:

Index Column1 Column2 2018 2019 2020
Index1 Name1 URL1
Index2 Name2 URL2 21.6 29.0 134.8
Index3 Name3 URL3

after that I want append a second and third dictionary of same form into the rows with Index: Index1 and then Index3.

What is the best way to do that with python?

CodePudding user response:

I think best is first create new DataFrame by indices and dictioanry and then add to original by DataFrame.join:

d = {'2018': 21.6, '2019': 29.0, '2020': 134.8}

df = df.join(pd.DataFrame([d], index=['Index2']))
print (df)
       Column1 Column2  2018  2019   2020
Index1   Name1    URL1   NaN   NaN    NaN
Index2   Name2    URL2  21.6  29.0  134.8
Index3   Name3    URL3   NaN   NaN    NaN

Or:

d = {'2018': 21.6, '2019': 29.0, '2020': 134.8}

df = df.join(pd.DataFrame.from_dict({'Index2': d}, orient='index'))
print (df)
       Column1 Column2  2018  2019   2020
Index1   Name1    URL1   NaN   NaN    NaN
Index2   Name2    URL2  21.6  29.0  134.8
Index3   Name3    URL3   NaN   NaN    NaN

CodePudding user response:

if you want to insert data into your dataframe with custom order you can try this:

import pandas as pd
df = pd.DataFrame([{'col1': 'Name1', 'col2': 'URL1'},{'col1': 'Name2', 'col2': 'URL2'},{'col1': 'Name3', 'col2': 'URL3'}],index=['Index1','Index2','Index3'])
d2 = {'2018': 21.6, '2019': 29.0, '2020': 134.8}
d1 = {'2018': 200, '2019': 29.0, '2020': 134.8}
d3 = {'2018': 500, '2019': 29.0, '2020': 134.8}
    
df = df.join(pd.DataFrame([d2,d1,d3], index=['Index2','Index1','Index3']))
print (df)

Output:

         col1  col2   2018  2019   2020
Index1  Name1  URL1  200.0  29.0  134.8
Index2  Name2  URL2   21.6  29.0  134.8
Index3  Name3  URL3  500.0  29.0  134.8
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