Closed MMenchero closed 2 months ago
The book uses fill_gaps
which creates NaN
s for times that were missing. plot_series
behaves the same way, i.e.
import pandas as pd
from utilsforecast.plotting import plot_series
from utilsforecast.preprocessing import fill_gaps
bank_calls = pd.read_csv(
'https://nixtla-public.s3.amazonaws.com/fpp4-datasets/bank_calls.csv',
parse_dates=['ds']
)
filled = fill_gaps(bank_calls, freq='5min', start='per_serie', end='per_serie')
plot_series(filled)
Closing due to lack of response.
Description
It would be nice to have the option of not plotting zero values when using the
plot_series
function when they're not relevant to the analysis.We could have an optional parameter, for example
exclude_zeros=True
, that allows users to choose whether to plot zero values.Use case
I'm currently working on the Python version of fpp4, specifically chapter 12.5, which involves plotting the number of calls to a bank, with no calls outside of operational hours.