如何将pandas Series编写为CSV作为行,而不是作为列?

时间:2022-02-16 15:49:44

I need to write a pandas.Series object to a CSV file as a row, not as a column. Simply doing

我需要将pandas.Series对象写为CSV文件作为行,而不是列。干脆做

the_series.to_csv( 'file.csv' )

gives me a file like this:

给我一个这样的文件:

record_id,2013-02-07
column_a,7.0
column_b,5.0
column_c,6.0

What I need instead is this:

我需要的是这样的:

record_id,column_a,column_b,column_c
2013-02-07,7.0,5.0,6.0

This needs to work with pandas 0.10, so using the_series.to_frame().transpose() is not an option.

这需要使用pandas 0.10,所以使用the_series.to_frame()。transpose()不是一个选项。

Is there a simple way to either transpose the Series, or otherwise get it written as a row?

是否有一种简单的方法可以转换系列,或者将其写成一行?

Thanks!

谢谢!

2 个解决方案

#1


13  

You can just use the DataFrame constructor (rather than to_frame):

您可以使用DataFrame构造函数(而不是to_frame):

In [11]: pd.DataFrame(s).T
Out[11]: 
record_id   column_a  column_b  column_c
2013-02-07         7         5         6

#2


0  

If you do not want line breaks:

如果你不想换行:

    df = pd.DataFrame({'record_id' : ['column_a','column_b','column_c'],
                       '2013-02-07' : [7.0, 5.0, 6.0]})
    str_1 = ', '.join(df.record_id.tolist())
    str_2 = ', '.join(str(x) for x  in df['2013-02-07'].tolist())

    print('record_id, ' + str_1)
    print('2013-02-07, ' + str_2)

#1


13  

You can just use the DataFrame constructor (rather than to_frame):

您可以使用DataFrame构造函数(而不是to_frame):

In [11]: pd.DataFrame(s).T
Out[11]: 
record_id   column_a  column_b  column_c
2013-02-07         7         5         6

#2


0  

If you do not want line breaks:

如果你不想换行:

    df = pd.DataFrame({'record_id' : ['column_a','column_b','column_c'],
                       '2013-02-07' : [7.0, 5.0, 6.0]})
    str_1 = ', '.join(df.record_id.tolist())
    str_2 = ', '.join(str(x) for x  in df['2013-02-07'].tolist())

    print('record_id, ' + str_1)
    print('2013-02-07, ' + str_2)