Here's an example:
Given that the dataset is a CSV file:
Column 1 Column 2 Column 3
Site # Type Value
0 A 0.358
0 B 12
1 B 84
1 A 3.879
1 B 4.823
0 A 9.7892
0 B 76.54
0 A 82
2 B 13.986
2 A 15.96
2 B 14.831
0 A 14
So what I would like to do is apply a function for all Site# = '0' to multiply the Value column by 13 or something and save that new table. Something like:
Column 1 Column 2 Column 3
Site # Type Value
0 A 4.654
0 B 156
1 B 84
1 A 3.879
1 B 4.823
0 A 127.2596
0 B 995.02
0 A 1066
2 B 13.986
2 A 15.96
2 B 14.831
0 A 182
Any and all help is greatly appreciated.
Use pandas
library.
>>> import pandas as pd
>>> import numpy as np
>>> df = pd.read_csv('csv_file')
>>> df.columns = ["Site", "Type", "Value"]
>>> df
Site Type Value
0 0 B 12.0000
1 1 B 84.0000
2 1 A 3.8790
3 1 B 4.8230
4 0 A 9.7892
5 0 B 76.5400
>>> df.Value = np.where(df.Site == 0, df.Value * 13, df.Value)
>>> df
Site Type Value
0 0 B 156.0000
1 1 B 84.0000
2 1 A 3.8790
3 1 B 4.8230
4 0 A 127.2596
5 0 B 995.0200
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