6]}df=pd.DataFrame(data)# Dictionary representing the new rownew_row={'A':4,'B':7}# Convert the dictionary to a DataFrame and then concatenate it with the original DataFramenew_df=pd.DataFrame([new_row])df=pd.concat([df,new_df],ignore_index=True)print(df)...
In [4]: df.loc[0, 'A'] = 1 In [5]: df Out[5]: A B C 0 1 NaN NaN Appending a row, given list of values: In [6]: df.loc[1] = [2, 3, 4] In [7]: df Out[7]: A B C 0 1 NaN NaN 1 2 3 4 Appending a row given a dictionary: In [8]: df.loc[2] = {...
Create a dictionary from a deep copy of a field in the feature layer, and update the values of this dictionary to reflect a new field: dols_field = dict(deepcopy(boundaries_lyr.properties.fields[1])) dols_field['name'] = "sovereignty_year" dols_field['alias'] = "SOVEREIGNTY_YEAR"...
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