How to “select distinct” across multiple data frame columns in pandas?

Question

I\'m looking for a way to do the equivalent to the SQL

SELECT DISTINCT col1, col2 FROM dataframe_table

The pandas sql comparison doesn\'t

Answer 1

There is no unique method for a df, if the number of unique values for each column were the same then the following would work: df.apply(pd.Series.unique) but if not then you will get an error. Another approach would be to store the values in a dict which is keyed on the column name:

In [111]:
df = pd.DataFrame({'a':[0,1,2,2,4], 'b':[1,1,1,2,2]})
d={}
for col in df:
    d[col] = df[col].unique()
d

Out[111]:
{'a': array([0, 1, 2, 4], dtype=int64), 'b': array([1, 2], dtype=int64)}