Species distribution data columns

[BioNCphilic]

I'm falling behind and having trouble with data columns. In the species-distribution-32-normalize data notebook. The column 'index_right' line 11 does not work the way it does in the textbook video. The error message is KeyError: "['index_right'] not in index"

[gpb3037]

I had problems too but went back to the video in https://cu-esiil-edu.github.io/esiil-learning-portal/foundations/notebooks/03-species-distribution/species-distribution.html and in the example this now works (after some other iterations)
NOTE some of my variable names may be different than yours...

gbif_ecoregion_gdf = (
eco_gdf
# Match the CRS of the GBIF data and the ecoregions
.to_crs(species_gbif_gdf.crs)
# Find ecoregion for each observation
.sjoin(
species_gbif_gdf,
how='inner',
predicate='contains')
# Select the required columns
[['gbifID','ECO_NAME','month']]
.reset_index()
.rename(columns={
'index': 'ecoregion',
'gbifID': 'observation_ID'})
)
gbif_ecoregion_gdf

[gpb3037]

shows up as this since I wanted to see the ecoregion name
ecoregion observation_ID ECO_NAME month
0 12 4743927038 Alberta-British Columbia foothills forests 5
1 12 4621947377 Alberta-British Columbia foothills forests 5
2 12 4761090115 Alberta-British Columbia foothills forests 6
3 12 4765238615 Alberta-British Columbia foothills forests 7
4 12 4630693711 Alberta-British Columbia foothills forests 6
... ... ... ... ...
159532 839 4633848077 North Atlantic moist mixed forests 10
159533 839 4749131402 North Atlantic moist mixed forests 9
159534 839 4763942306 North Atlantic moist mixed forests 9
159535 839 4746476478 North Atlantic moist mixed forests 9
159536 839 4719267065 North Atlantic moist mixed forests 9

[BioNCphilic]

Yep - tried that and based upon the textbook vide, eco name has the same issue as some other columns in that the values are repeated and not unique to each entry.

[gpb3037]

But then my next section doesn't work with observation_ID derived from my gbifID so something also still wierd.

[gpb3037]

it was because I didnt have square brackets in the next section
I had .groupby('ecoregion','month')
when I should have had
.groupby(['ecoregion', 'month'])
so now this code works to do the summaries with that above:

chatgpt version - aha I was missing square brackets in syntax

Grouping data by ecoregion and month, and counting occurrences

occurrence_df = (
gbif_ecoregion_gdf
# Group by both ecoregion and month
.groupby(['ecoregion', 'month'])
# Count the number of occurrences
.agg(occurrences=('observation_id', 'count'))
.reset_index() # Resetting index to have a proper DataFrame
)

occurrence_df

[gpb3037]

all of this stuff may be in error for gbfID vs OBJECT_ID as I see later in the video!

[BioNCphilic]

OBJECTID has the same issue - there are no unique identifiers that I could find on the ecoregion_gdf dataset. I also tried ECO_NAME, ECO_BIOME_, ECO_ID, and finally NNH before throwing my hands up (instead of smashing the computer!). Hopefully class today will help. Thanks @gpb3037

[eculler]

@BioNCphilic @gpb3037 was this issue solved in office hours? If not let me know.

I am still not sure what caused this issue in the first place, since it seems to work the first time through and then fail when the same code is run again. But it seems like making sure that the column names do match with existing column names fixes it? 'index_right' is something that gets created automatically when joining with something other than the index.

Also note that in the second video we go through how to fix this. I will correct the first video in a few weeks, but for now I want to make sure that the videos match -- so go ahead and go through all of them to fix this issue.

[BioNCphilic]

Thanks for the help with this. I think I've got it figured out.