How to change order of rows in dataframe

Question

When I import my data using pd.read_csv() from designated folder where all files are ordered in alphabetical order (ex. A1, A2, A3, A4, ..., A12, B1, B2, ..., B12), the rows created in dataframe are in order of (A1, A10, A11, A12, A2, A3, A4, A5, A6,...,A9, B1, B10, B11, B12, B2, ..., B9). So A10, A11, A12 come before A2. Do you know how to import the data in an order I want?

It looks like this:

data = {
   'Order':['A1', 'A10', 'A11', 'A12', 'A2', 'A3' ,'A4' ,'A5' ,'A6' ,'A7' ,'A8', 'A9',
               'B1', 'B10', 'B11', 'B12', 'B2', 'B3' ,'B4' ,'B5' ,'B6' ,'B7' ,'B8', 'B9']}

Does this answer your question? [Keeping columns in the specified order when using UseCols in Pandas Read\_CSV](https://stackoverflow.com/questions/40024406/keeping-columns-in-the-specified-order-when-using-usecols-in-pandas-read-csv) — dsanatomy, Sep 02 '20 at 10:03

score 5 · Answer 1 · answered Sep 02 '20 at 10:01

Try splitting out the text from the numerical part of the string using str.extract - casting the numerical part to an int dtype. Then sort of both columns and use reindex to sort the DataFrame:

df = pd.DataFrame(data)

df.reindex(
    df.Order.str.extract(r'^(.*?)(\d+)$')
    .astype({1:'int'})
    .sort_values([0, 1])
    .index)

[out]

How to change order of rows in dataframe

1 Answers1