Forecasting with Prophet

General
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1

I have this data with daily entries from (2021/04 - 2021/10). Where I have 78 different locations. I am interested to forecast each one of them for the next 3 months using prophet. Please help me to resolve my error.

Here is the code:

model_data <- data1 %>%
  dplyr::select(date, pred, level2code)

Selecting all the 78 locations

key <- model_data %>%
  select(level2code) %>%
  distinct() %>%
  mutate(name = c(1:78))  

model_results <- data.frame()

    for (i in 1:78){
  model <- data1 %>%
    filter(level2code == key$level2code[i]) %>%
    select(date, y = pred) %>%
    prophet()
  assign(paste(key$name[i], "model", sep = "_"), model)

  Predicted_values <- make_future_dataframe(model, periods = 90)

  results <- predict(model, Predicted_values) %>%
    select(date, yhat_lower, yhat_upper, yhat) %>%
    mutate(level2code = key$level2code[i],
           date = as.Date(date)) %>%
    inner_join(data1, by = c("level2code" = "level2code", "date" = "date"))
  model_results <- rbind(model_results, results)
}

But, I get this error:

Error in fit.prophet(m, df, ...) : 
  Dataframe must have columns 'ds' and 'y' with the dates and values respectively

Sample Data set:

date    product level2code  pred
2021-04-01  garri   NG020001    366.1540473
2021-04-01  garri   NG020002    393.3557317
2021-04-01  garri   NG020003    374.3132972
2021-04-01  garri   NG021001    353.1266783
2021-04-01  garri   NG021002    329.9673004
2021-04-01  garri   NG021003    391.1370065
2021-04-01  garri   NG021004    306.1356683
2021-04-01  garri   NG020004    372.8115048
2021-04-01  garri   NG020005    350.0100309
2021-04-01  garri   NG021005    373.0025842
2021-04-01  garri   NG020006    383.1839042
2021-04-01  garri   NG021006    383.5212653
2021-04-01  garri   NG020007    486.8226379
2021-04-01  garri   NG020008    334.8151487
2021-04-01  garri   NG021007    379.89125
2021-04-01  garri   NG021008    370.9376296
2021-04-01  garri   NG021009    389.4640031
2021-04-01  garri   NG021010    365.9266992
2021-04-01  garri   NG020009    380.4655716
2021-04-01  garri   NG020010    352.6139069
2021-04-01  garri   NG020011    243.5701952
2021-04-01  garri   NG021011    366.6883205
2021-04-01  garri   NG021012    326.9402671
2021-04-01  garri   NG020012    403.5666062
2021-04-01  garri   NG021013    405.2860516
2021-04-01  garri   NG021014    348.023662
2021-04-01  garri   NG020013    372.7586167
2021-04-01  garri   NG020014    392.5432373
2021-04-01  garri   NG020015    362.1098193
2021-04-01  garri   NG020016    343.9205353
2021-04-01  garri   NG020017    366.5290601
2021-04-01  garri   NG020018    431.0832709
2021-04-01  garri   NG020019    411.3581413
2021-04-01  garri   NG021015    348.3274897
2021-04-01  garri   NG021016    336.3743799
2021-04-01  garri   NG020020    393.8901327
2021-04-01  garri   NG021017    391.7393648
2021-04-01  garri   NG021018    346.0988762
2021-04-01  garri   NG021019    346.1310667
2021-04-01  garri   NG021020    359.2837766
2021-04-01  garri   NG020021    450.4413674
2021-04-01  garri   NG020022    373.6406838
2021-04-01  garri   NG021021    420.0838824
2021-04-01  garri   NG020023    408.6912783
2021-04-01  garri   NG020024    285.8249281
2021-04-01  garri   NG020025    388.3307999
2021-04-01  garri   NG020026    365.1686898
2021-04-01  garri   NG020027    391.6867595
2021-04-01  garri   NG021022    384.1850593
2021-04-01  garri   NG021023    397.7172044
2021-04-01  garri   NG020028    331.2182171
2021-04-01  garri   NG021024    393.323333
2021-04-01  garri   NG020029    405.5813127
2021-04-01  garri   NG021025    359.658715
2021-04-01  garri   NG021026    370.3166839
2021-04-01  garri   NG021027    391.088788
2021-04-01  garri   NG021028    364.2770249
2021-04-01  garri   NG020030    375.2600611
2021-04-01  garri   NG021029    358.9618615
2021-04-01  garri   NG020031    439.1322423
2021-04-01  garri   NG020032    402.7340519
2021-04-01  garri   NG021030    345.2253201
2021-04-01  garri   NG020033    356.2798309
2021-04-01  garri   NG020034    369.3260162
2021-04-01  garri   NG021031    368.6820545
2021-04-01  garri   NG021032    342.8985896
2021-04-01  garri   NG021033    388.3937476
2021-04-01  garri   NG020035    369.5370586
2021-04-01  garri   NG020036    374.2149029
2021-04-01  garri   NG020037    374.3105323
2021-04-01  garri   NG020038    419.9881972
2021-04-01  garri   NG020039    356.6891081
2021-04-01  garri   NG020040    385.9381759
2021-04-01  garri   NG020041    308.1801669
2021-04-01  garri   NG020042    383.1544687
2021-04-01  garri   NG020043    381.4891835
2021-04-01  garri   NG020044    362.6149694
2021-04-01  garri   NG021034    351.0315915
2

Try one of these

# using rename
model_data <- data1 %>%
  select(date, pred, level2code, product) %>%
  rename(ds = date) %>%
  select(level2code, ds, pred)

# shorter - just renaming within select
model_data <- data1 %>%
# not sure what your other select was for
  select(level2code, ds = date, pred)

Also have a look at providing a better reproducible dataset as yours is not:

3

I have made some changes in the code but now I get a different error, please see it at the end. It says the data frame must have ds and y, I have both of them, Don't know why it's not working.

4

I do not see ds anywhere in your code.

5

yes, I have changed the name of the date column to ds in the CSV file and it works fine. Thanks for replying.

6

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