Why cannot pivot_table a non numeric column?

Im trying this code

df_aggregated[['modeWinddirectiondiscrete','CAMPAÑA', 'ID_ESTACION','Month']].pivot_table(index=['CAMPAÑA', 'ID_ESTACION'], columns='Month')

Where the column 'modeWinddirectiondiscrete' have values like "North, West, South, East ..."

And I have as result just the index. I tried it with other numeric columns and works well so the problem is that the column has Strings. Is it possible to have a correct solution with the Strings? or I need to transform the directions to numbers?

EDIT:
For example I have this table

mode  modeWinddirectiondiscrete  CAMPAÑA  ID_ESTACION  Month
    0                     South       16            0      1
    1                     North       16            0      1
    2                     North       16            0      1
    3                     East        16            0      2
    4                     West        16            0      2
    5                     East        16            0      2
    6                     South       17            1      3
    7                     West        17            1      3
    8                     North       17            1      3
    9                     West        17            1      3

And i want something like:

                                                   DewpointLocalDayAvg
              Month   1   10   11   12   2   3   4   5   6   7   8   9
CAMPAÑA	ID_ESTACION
     16           0 North .............East...........................
     17           1 .......................West.......................

The result must be something like that, I don't know if this example is well understood.

What about this?

import pandas as pd

# toy dataset
data = {
    'modeWinddirectiondiscrete': ['North', 'South', 'East', 'West', 'North'],
    'CAMPAÑA': [1, 1, 2, 2, 3],
    'ID_ESTACION': [1, 2, 1, 2, 3],
    'Month': ['January', 'February', 'January', 'February', 'January']
}

df_aggregated = pd.DataFrame(data)

# turn modeWinddirectiondiscrete into categorical data (equivalent of factors in R)
df_aggregated['modeWinddirectiondiscrete'] = pd.Categorical(df_aggregated['modeWinddirectiondiscrete'], categories=['North', 'South', 'East', 'West'])

df_aggregated.pivot_table(index=['CAMPAÑA', 'ID_ESTACION'], columns='Month', values='modeWinddirectiondiscrete', aggfunc='first')

Month               February January
CAMPAÑA ID_ESTACION                 
1       1                NaN   North
        2              South     NaN
2       1                NaN    East
        2               West     NaN
3       3                NaN   North

Let me know if this doesn't work for the actual data, and I'll update it

Update: ouroboros1 helpfully pointed out that the issue with your code is that pivot_table defaults to aggregating values using their mean, which doesn't make any sense for categorical data, as the categories don't correspond to numbers which can be averaged.

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