Closed exprez135 closed 3 years ago
It appears that data from employees of Columbia Southern University was accidentally in this analysis.
df.loc[df.contributor_employer == "COLUMBIA SOUTHERN UNIVERSITY"] yields 259 contributions totaling $23,950.30.
df.loc[df.contributor_employer == "COLUMBIA SOUTHERN UNIVERSITY"]
There is also someone who misspelled their employer as "UNIVERSITY OF BRIRISH COLUMBIA" so that the filter for British didn't catch it.
Other than that, I found no anomalous data. Could probably be rooted out by adding "SOUTHERN" and "BRIRISH" to the faux list?
southern.csv.txt
Note: this is from looking at 2019-2020 data from 2020_final.ipynb. Didn't check 2016 data at all.
@exprez135 Thanks for catching this! Working on updating
It appears that data from employees of Columbia Southern University was accidentally in this analysis.
df.loc[df.contributor_employer == "COLUMBIA SOUTHERN UNIVERSITY"]
yields 259 contributions totaling $23,950.30.There is also someone who misspelled their employer as "UNIVERSITY OF BRIRISH COLUMBIA" so that the filter for British didn't catch it.
Other than that, I found no anomalous data. Could probably be rooted out by adding "SOUTHERN" and "BRIRISH" to the faux list?
southern.csv.txt