熊猫-标题中缺少值的read_csv

Question

I have this kind of csv file:

date,a,b,c
2014,12,29,7,12,45
2014,12,30,7,13,12
2014,12,31,6.5,6,5

So the first row does not explicitly specify all columns, and kind of assumes that you understand that the date is the first 3 columns.

How do I tell read_csv to consider the first three columns as one date column (while keeping the other labels)?

Answer 1

You can parse your columns directly as a date, if you use the parse_dates argument.

From the docs :

parse_dates : boolean, list of ints or names, list of lists, or dict, default False

If True -> try parsing the index. If [1, 2, 3] -> try parsing columns 1, 2, 3 each as a separate date column. If [[1, 3]] -> combine columns 1 and 3 and parse as a single date column. {'foo' : [1, 3]} -> parse columns 1, 3 as date and call result 'foo' A fast-path exists for iso8601-formatted dates.

For your file, you can do something like this:

pd.read_csv(file_path, names=['y', 'm', 'd', 'a', 'b', 'c'], header=0,
    parse_dates={'date': [0, 1, 2]}, index_col='date', )

              a   b   c
date                   
2014-12-29  7.0  12  45
2014-12-30  7.0  13  12
2014-12-31  6.5   6   5

The thing with the missing values in headline is solved by passing the names argument and header=0 (to overwrite the existing header). Then it is possible to specify which columns should be parsed as a date.

See another example here .