I have a pandas DataFrame with 3 columns : product
, region
, and cost
.
I want to display a pivot table using pivottable.js in a Jupyter notebook such that product
are rows, region
are columns and cost
are values.
I have tried :
from pivottablejs import pivot_ui
import pandas as pd
df = pd.DataFrame({'region':['N', 'S', 'W', 'E', 'N', 'S', 'W', 'E'],
'product':['P1', 'P1', 'P1', 'P1', 'P2', 'P2', 'P2', 'P2'],
'cost':[10, 13, 17, 28, 29, 23, 17, 18]})
pivot_ui(df, rows=['product'], cols=['region'], values=['cost'])
But this does not work, since there does not exist a values
attribute for pivot_ui()
.
How to do that ?
The first problem is that this function doesn't accept a
values
kwarg, but rathervals
.The second issue you'll face is that you'll need to specify an aggregation function (the default is
Count
) to summarize your values. This is sort of similar to thepandas
pivot table'saggfunc
argument. If you expect to only have a single value then something likepivot_ui(df, rows=['product'], cols=['region'], vals=['cost'], aggregatorName='First')
should do the trick.By way of explanation, your code above is just providing the
Count
of input records per cell.Count
doesn't accept any arguments, so passing invals
on its own won't change that.First
does accept arguments, so passing invals=['cost']
will cause each cell to contain the first value ofcost
(ordered via "natural sort") per cell.