appending multi index columns into empty dataframe

Question

Following Problem I got a DataFrame like so:

df = pd.DataFrame(columns=pd.MultiIndex(levels=[["foo","baa"],["x","y","z"]], labels=[[0,0,0,1,1,1],[0,1,2,0,1,2]]), index=[0,1,2,3], data=np.random.rand(4,6))

         foo                           baa                    
          x         y         z         x         y         z
0  0.263780  0.942880  0.176744  0.914854  0.920735  0.573692
1  0.601317  0.584691  0.288536  0.832064  0.095142  0.186045
2  0.807323  0.075620  0.399703  0.936894  0.168441  0.468984
3  0.871293  0.324817  0.395784  0.133541  0.365586  0.615219

And I want to get say foo out of it into a new DataFrame completly empty constructed like this:

r_df = pd.DataFrame(index=df.index)
Empty DataFrame
Columns: []
Index: [0, 1, 2, 3]

it should look like this:

         foo
          x         y         z
0  0.263780  0.942880  0.176744
1  0.601317  0.584691  0.288536
2  0.807323  0.075620  0.399703
3  0.871293  0.324817  0.395784

How I tryed to do it was like this:

for label in df.columns.levels[0]:
    data = df[label]
    for row in data.index:
        r_df.loc[row,(label,"x")] = data["x"]
        r_df.loc[row,(label,"y")] = data["y"]
        r_df.loc[row,(label,"z")] = data["z"]

I thought this could work because multi index can be referenced by tubles but it didnt.

that is not the problam I need to not print but work on the data — PapaTim68
– PapaTim68, Commented Oct 10, 2018 at 9:50
You can create new dataframe out of the existing one :- dfnew=df['foo'] — Developer
– Developer, Commented Oct 10, 2018 at 9:52
You can also use r_df = df.xs('foo', axis=1, level=0, drop_level=False) if you do want to keep it as a multiindex. — gyx-hh
– gyx-hh, Commented Oct 10, 2018 at 9:59
If you are satisfied by answer please mark it accepted...let me know if you need any other information. — Developer
– Developer, Commented Oct 10, 2018 at 9:59

gyx-hh · Accepted Answer · 2018-10-10 10:13:47Z

1

Try the following using df.xs to select from multiIndex and keep level:

r_df = df.xs('foo', axis=1, level=0, drop_level=False)

If you want to append a new column under foo then you can do:

df.loc[:,('foo','m')] = 0

if you want to a append a new column in level=0 (same level as foo)

# with no col in level 1
df.loc[:, 'bar'] = 0 

# with col in level 0 and 1
df.loc[:,('bar','m')] = 0

answered Oct 10, 2018 at 10:13

gyx-hh

1,4411 gold badge12 silver badges15 bronze badges

Sign up to request clarification or add additional context in comments.

Collectives™ on Stack Overflow

appending multi index columns into empty dataframe

1 Answer 1

Comments

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

Comments

Related