Adding values to dataframe columns based on value from a single column

Question

I have a DataFrame with yearly kg/ha values in which the columns reach from 1950 to 2015. The first column are gridcodes (gridcode_1) reaching from 1 to 4. Every gridcode has a specific addition value I want to add to the kg/ha values of the other columns.

I tried to solve it via for loop and regular expression

for x in kilograms_dep2:
    if kilograms_dep2['gridcode_1'] == 1:
        kilograms[regex="[0-9]{4}"] + 2.7
    elif kilograms_dep2['gridcode_1'] == 2:
        kilograms_dep2[regex="[0-9]{4}"] + 16.04
    elif kilograms_dep2['gridcode_1'] == 3:
        kilograms_dep2[regex="[0-9]{4}"] + 2.7
    elif kilograms_dep2['gridcode_1'] == 4:
        kilograms_dep2[regex="[0-9]{4}"] + 0.75

but it would only result in syntax errors.

Here are the first few entries of the dataframe

 gridcode_1         1950_y         1951_y         1952_y         1953_y
          1    1477.273256    1477.273256    1477.273256    1477.273256
          2  523883.351859  523883.351859  523883.351859  523883.351859
          3    2698.864601    2698.864601    2698.864601    2698.864601
          4    6458.175014    6458.175014    6458.175014    6458.175014

so for gricode_1 = 1 I want to add 2.7, for gridcode_1 = 2 I want to add 16.04 etc.

I'd appreciate every help for an elegant solution.

ncica · Accepted Answer · 2019-09-25 14:06:58Z

1

columns_list  = list(df.columns)
columns_list.remove('code')

df.loc[(df['code'] == 1 ),columns_list] = df.loc[(df['code'] == 1),columns_list] + 2.7

df.loc[(df['code'] == 2 ),columns_list] = df.loc[(df['code'] == 2),columns_list] + 16.04

result:

edited Sep 25, 2019 at 14:06

ncica

7,2161 gold badge19 silver badges41 bronze badges

answered Sep 25, 2019 at 11:39

raj

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