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# List unique values in a DataFrame column | |
df['Column Name'].unique() | |
# To extract a specific column (subset the dataframe), you can use [ ] (brackets) or attribute notation. | |
df.height | |
df['height'] | |
# are same thing!!! (from http://www.stephaniehicks.com/learnPython/pages/pandas.html | |
# -or- | |
# http://www.datacarpentry.org/python-ecology-lesson/02-index-slice-subset/) |
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university | total_salary | |
---|---|---|
Chicago State University | 26643267.07 | |
Eastern Illinois University | 39104962.4 | |
Governors State University | 27282001.7 | |
Illinois State University | 92108974.46 | |
Northeastern Illinois University | 38303671.72 | |
Northern Illinois University | 93582392.05 | |
Southern Illinois University Carbondale | 74338384.24 | |
Southern Illinois University Edwardsville | 64287003.19 | |
Southern Illinois University School of Medicine | 72072277.63 |
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id | generalcommodity | date | value | |
---|---|---|---|---|
0 | Refuse | 2016-01-02 | 3372.0 | |
1 | Refuse | 2016-01-03 | 36.0 | |
2 | Refuse | 2016-01-04 | 3366.0 | |
3 | Refuse | 2016-01-05 | 3543.0 | |
4 | Refuse | 2016-01-06 | 3461.0 | |
5 | Refuse | 2016-01-07 | 3340.0 | |
6 | Refuse | 2016-01-08 | 3149.0 | |
7 | Refuse | 2016-01-09 | 30.0 | |
8 | Refuse | 2016-01-10 | 43.0 |
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nuid | id | total | year | |
---|---|---|---|---|
0 | 4139 | 1 | 2015 | |
1 | 4141 | 3 | 2013 | |
2 | 4146 | 2 | 2012 | |
3 | 4159 | 2 | 2012 | |
4 | 4157 | 18 | 2016 | |
5 | 4156 | 3 | 2017 | |
6 | 4156 | 1 | 2019 | |
7 | 4156 | 1 | 2018 | |
8 | 4183 | 1 | 2012 |
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