pandas catagorises

分类Categoricals
Since version 0.15, pandas can include categorical data in a DataFrame. For full docs, see thecategorical introduction and theAPI documentation.

In [122]: df = pd.DataFrame({"id":[1,2,3,4,5,6], "raw_grade":['a', 'b', 'b', 'a', 'a', 'e']})
Convert the raw grades to a categorical data type.

In [123]: df["grade"] = df["raw_grade"].astype("category")

In [124]: df["grade"]
Out[124]: 
0    a
1    b
2    b
3    a
4    a
5    e
Name: grade, dtype: category
Categories (3, object): [a, b, e]
Rename the categories to more meaningful names (assigning to Series.cat.categories is inplace!)

In [125]: df["grade"].cat.categories = ["very good", "good", "very bad"]
Reorder the categories and simultaneously add the missing categories (methods underSeries.cat return a newSeries per default).

In [126]: df["grade"] = df["grade"].cat.set_categories(["very bad", "bad", "medium", "good", "very good"])

In [127]: df["grade"]
Out[127]: 
0    very good
1         good
2         good
3    very good
4    very good
5     very bad
Name: grade, dtype: category
Categories (5, object): [very bad, bad, medium, good, very good]
Sorting is per order in the categories, not lexical order.

In [128]: df.sort_values(by="grade")
Out[128]: 
   id raw_grade      grade
5   6         e   very bad
1   2         b       good
2   3         b       good
0   1         a  very good
3   4         a  very good
4   5         a  very good
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