I have the following dataframe:
fid via
2015-01-18 id_22207 0.275056
2015-01-30 id_22207 0.306961
2015-02-23 id_22207 0.285065
2015-02-24 id_22207 0.337570
2015-02-27 id_22207 0.311612
2015-01-18 id_22208 0.371765
2015-01-20 id_22208 0.405391
2015-02-11 id_22208 0.354052
2015-02-24 id_22208 0.421126
2015-03-15 id_22208 0.454406
I want to use this dataframe to do time-series forecasting using facebook's prophet
library. Is there a way in that library to use this dataframe? The tricky part is that I have multiple fid values, and for each fid I have data in the via
column for multiple dates. I want to do forecasting for via
column for the foll. dataframe:
2015-03-18 id_22209
2015-03-20 id_22209
2015-03-21 id_22209
2015-03-24 id_22209
2015-03-25 id_22209
Currently, prophet
does not support multivariate time-series forecasting or VAR. Your best bet is to create forecasts in a loop after splitting the data frame based on the fid
column.
library(tidyverse)
library(prophet)
lapply(split(df, f= df$fid), function(x) {
# Prophet expects columns to be ds, y
x <- x %>% rename(y = via, ds = date)
# Create prophet forecasts
# ...
})
EDIT
Didn't notice this question was tagged as Python.
unique_fid = df['fid'].unique()
for fid in unique_fid:
temp_df = df.loc[df['fid'] == fid,['date', 'via']]
# Prophet expects ds and y as columns
temp_df.columns = ['ds', 'y']
# Create prophet forecasts
# ...