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I have to read several files some in Excel format and some in CSV format. Some of the files have hundreds of columns.
Is there a way to select several ranges of columns without specifying all the column names or positions? For example something like selecting columns 1 -10, 15, 17 and 50-100:
df = df.ix[1:10, 15, 17, 50:100] I need to know how to do this both when creating dataframe from Excel files and CSV files and after the data framers created.
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Using df[] & loc[] to Select Multiple Columns by NameBy using df[] & pandas. DataFrame. loc[] you can select multiple columns by names or labels. To select the columns by names, the syntax is df.
To slice the columns, the syntax is df. loc[:,start:stop:step] ; where start is the name of the first column to take, stop is the name of the last column to take, and step as the number of indices to advance after each extraction; for example, you can select alternate columns.
use np.r_
np.r_[1:10, 15, 17, 50:100] array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 15, 17, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99]) so you can do
df.iloc[:, np.r_[1:10, 15, 17, 50:100]] If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
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