Flatten a pandas dataframe to a single column or a series

I have a dataframe

import pandas as pd
df = pd.DataFrame([[2, 1,5], [8, 3,4]],
                                    index=['cat', 'dog'],
                                    columns=['weight', 'height', 'blood_pressure'])

This is how I flatten it to a single column. I wonder whether there is a better way

id1 = pd.MultiIndex.from_product([df.index, df.columns], names=('animal', 'measure'))
df2 = pd.DataFrame(np.array(df).reshape(len(df)*len(df.columns),1), index = id1)

Is there any way to get a series from the single dataframe column? Thanks!

A dataframe column is a pd.Series. So, I don’t quite get your question. What is it you want to do (what’s the purpose of the flattening/multi-index creation)?

I want to represent a 3-dimensional dataset by a typical (2-dimensional) dataframe. You are right, a single dataframe column would work. Thank you so much Hans!

So, the rows are also pd.Series objects, so you could also consider just doing df.T (df.transpose()) to convert the original df:

                cat  dog
weight            2    8
height            1    3
blood_pressure    5    4

It all depends on what kind of further processing you want to do…

Just to clarify, the problem I have is that I have zoo 1, zoo 2, zoo 3, … For each zoo, I have a cat and a dog, and I have their data (weight, height, blood_pressure). Since it’s hard to visualize the 3-dimensional data, I try to convert the dataframe for each zoo to a column, so that I may show all data in a typical 2-dimensional dataframe.