Does Pandas `concat` method ignore the `axis` parameter, when concatenating a DataFrame with a Serie-CodePudding

I created a Series object.

for index, entry in a_data_frame.iterrows():
    ...

Then I would like to concatenate this series to a new/another data frame. My goal is to build up the new data frame based on some unique recombination of the rows in the previous one.

concatenated_data = pandas.concat((concatenated_data, concat_entry))

The series will be appended to the end of the columns disregarding the value of the axis parameter. Why?

CodePudding user response：

My experiments allow me to assume that Pandas "thinks" series as columns. When I convert a series to a data frame, it will result in a frame with a single column.

concat_entry.to_frame()

It makes sense to me that I was unable to use (to concatenate) this series ("column") with a data frame as a "row". The simplest solution is to transpose the new data frame before concatenation.

concat_entry.to_frame().transpose()

concatenated_data = pandas.concat((concatenated_data, concat_entry.to_frame().transpose()))

CodePudding user response：

It's hard to tell what your code is actually doing, but if you want to resample a Dataframe or a Series you can use the .sample() method.

series = pd.Series([1,2,3,4,5])
series.sample(len(series))

Output

2    2
0    1
4    2
1    1
3    2
Name: Path Id, dtype: object