Replacing a nested dictionary into empty dataframe

Question

I have the following nested_dict:

{'view_0': {'spain': -1}, 'view_1': {'portugal': 0}, 'view_2': {'morocco': 1.0, 'france': -1.0}, 'view_3': {'germany': 0.5, 'italy': 0.5, 'uk': -0.5, 'ireland': -0.5}}

On the other side, I have the following empty_df, wherein the index appears the keys of the nested_dict. and in the columns the key found in the values of each nested_dict.

            spain  portugal  morocco  france  germany  italy  uk   ireland
view_0          0    0         0        0       0       0      0      0             
view_1          0    0         0        0       0       0      0      0       
view_2          0    0         0        0       0       0      0      0       
view_3          0    0         0        0       0       0      0      0

I would like to place the values.values() of nested_dict in the empty_df to obtain the following output:

            spain  portugal  morocco  france  germany  italy  uk   ireland
view_0         -1    0         0        0       0       0      0      0             
view_1          0    0         0        0       0       0      0      0       
view_2          0    0         1       -1       0       0      0      0       
view_3          0    0         0        0      0.5     0.5   -0.5   -0.5

And in order to do so I tried a

empty_df.replace(nested_dict)

However returns the empty_dict filled with zeros, not substituting the values.

jezrael · Accepted Answer · 2018-10-23 10:43:43Z

1

If possible use DataFrame.from_dict and replace empty values by fillna:

df = pd.DataFrame.from_dict(d, orient='index').fillna(0)

Also is possible add reindex for same columns and index names in same ordering like empty_df:

df = (pd.DataFrame.from_dict(d, orient='index')
                  .reindex(columns=empty_df.columns, index=df_empty.index)
                  .fillna(0))

print (df)
        spain  portugal  morocco  france  germany  italy   uk  ireland
view_0   -1.0       0.0      0.0     0.0      0.0    0.0  0.0      0.0
view_1    0.0       0.0      0.0     0.0      0.0    0.0  0.0      0.0
view_2    0.0       0.0      1.0    -1.0      0.0    0.0  0.0      0.0
view_3    0.0       0.0      0.0     0.0      0.5    0.5 -0.5     -0.5

answered Oct 23, 2018 at 10:43

jezrael

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jpp · Accepted Answer · 2018-10-23 10:48:03Z

1

Construct a dataframe from your dictionary and use pd.DataFrame.update:

df_data = pd.DataFrame.from_dict(d, orient='index')

df.update(df_data)

print(df)

        spain  portugal  morocco  france  germany  italy   uk  ireland
view_0   -1.0       0.0      0.0     0.0      0.0    0.0  0.0      0.0
view_1    0.0       0.0      0.0     0.0      0.0    0.0  0.0      0.0
view_2    0.0       0.0      1.0    -1.0      0.0    0.0  0.0      0.0
view_3    0.0       0.0      0.0     0.0      0.5    0.5 -0.5     -0.5

answered Oct 23, 2018 at 10:48

jpp

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