hydro2023 fix

[bczernecki]

Hot fixes for monthly and daily hydro dataset that include different encodings and seperator characters.

[codecov[bot]]

Codecov Report

Attention: Patch coverage is 94.38202% with 5 lines in your changes missing coverage. Please review.

Project coverage is 87.83%. Comparing base (68af360) to head (5415429). Report is 1 commits behind head on master.

Files with missing lines	Patch %	Lines
R/hydro_imgw_daily.R	95.45%	2 Missing :warning:
R/hydro_imgw.R	0.00%	1 Missing :warning:
R/hydro_metadata_imgw.R	0.00%	1 Missing :warning:
R/nearest_stations_imgw.R	0.00%	1 Missing :warning:

Additional details and impacted files

@@            Coverage Diff             @@
##           master     #100      +/-   ##
==========================================
+ Coverage   83.71%   87.83%   +4.11%     
==========================================
  Files          32       29       -3     
  Lines        1750     1619     -131     
==========================================
- Hits         1465     1422      -43     
+ Misses        285      197      -88     

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[bczernecki]

@Nowosad ready for re-review

[Nowosad]

devtools::load_all()
#> ℹ Loading climate
h2022 = hydro_imgw_monthly(2022)
#> /tmp/Rtmphey1As/file196d36654abf4
#> /tmp/Rtmphey1As/file196d32351d8f5
#> /tmp/Rtmphey1As/file196d356036c71
h2023 = hydro_imgw_monthly(2023)
#> /tmp/Rtmphey1As/file196d3341d7c9e
#> /tmp/Rtmphey1As/file196d31bb006c6
#> /tmp/Rtmphey1As/file196d36f58fb13
h2024 = hydro_imgw_monthly(2024)
#> /tmp/Rtmphey1As/file196d34142d196
#> Problems with downloading data. Run function with argument allow_failure = FALSE to see more details

One question @bczernecki -- no data for 2024 exist yet?

[bczernecki]

One question @bczernecki -- no data for 2024 exist yet?

Not yet

[Nowosad]

One more question -- why meteo_imgw_datastore() returns a data.table and the rest (?) of the functions return a regular data frame? Is there a reason for this inconsistency?

[bczernecki]

One more question -- why meteo_imgw_datastore() returns a data.table and the rest (?) of the functions return a regular data frame? Is there a reason for this inconsistency?

This is the largest of all datasets (10-min time resolution) and it is based on data.table which is significantly faster. On the other hand it has consistent structure contrary to other IMGW datasets which varies in terms of columns order, etc... so this is exception only for this dataset. However, we can think about wrapping it into as.data.frame() before return statement