How to Update Value in First N Rows by Group in a Multi-Index Pandas Dataframe?

Question

I am attempting to update the first N rows in a multi-index dataframe but was having a bit of trouble finding a solution so thought I\'d create a post for it.

The exampl

Answer 1

How about this - first define a function that takes a dataframe, and replaces the first x records with a specified value.

def replace_first_x(group_df, x, value):
    group_df.iloc[:x, :] = value
    return group_df

Then, pass that into the groupby object with apply.

In [97]: df.groupby(level=0).apply(lambda df: replace_first_x(df, 2, 9999))
Out[97]: 
                               A            B            C            D
CATEGORY DATE                                                          
A        2000-01-01  9999.000000  9999.000000  9999.000000  9999.000000
         2000-01-03  9999.000000  9999.000000  9999.000000  9999.000000
         2000-01-05     1.590503     0.948911    -0.268071     0.622280
         2000-01-07    -0.493866     1.222231     0.125037     0.071064
B        2000-01-02  9999.000000  9999.000000  9999.000000  9999.000000
         2000-01-04  9999.000000  9999.000000  9999.000000  9999.000000
         2000-01-06     1.663430    -1.170716     2.044815    -2.081035
         2000-01-08     1.593104     0.108531    -1.381218    -0.517312

Answer 2

Typically, whenever you have to change values, rather then just pick them, you cannot proceed using a lambda function only, since these only allow selection.

A very boiled down way to proceed is

def replace_first(group):
    group.iloc[0:2] = 99
    return group

and then just do

In[144]: df.groupby(level=0).apply(replace_first)
Out[144]: 
                             A          B          C          D
CATEGORY DATE                                                  
A        2000-01-01  99.000000  99.000000  99.000000  99.000000
         2000-01-03  99.000000  99.000000  99.000000  99.000000
         2000-01-05   0.458031   1.959409   0.622295   0.959019
         2000-01-07   0.934521  -2.016685   1.046456   1.489070
B        2000-01-02  99.000000  99.000000  99.000000  99.000000
         2000-01-04  99.000000  99.000000  99.000000  99.000000
         2000-01-06  -0.117322  -1.664436   1.582124   0.486796
         2000-01-08  -0.225379   0.794846  -0.021214  -0.510768