Value Label in pandas?

Question

I am fairly new to pandas and come from a statistics background and I am struggling with a conceptual problem: Pandas has columns, who are containing values. But sometimes values have a special meaning - in a statistical program like SPSS or R called a "value labels".

Imagine a column rain with two values 0 (meaning: no rain) and 1 (meaning: raining). Is there a way to assign these labels to that values?

Is there a way to do this in pandas, too? Mainly for platting and visualisation purposes.

Answer 1

There's not need to use a map anymore. Since version 0.15, Pandas allows a categorical data type for its columns. The stored data takes less space, operations on it are faster and you can use labels.

I'm taking an example from the pandas docs:

df = pd.DataFrame({"id":[1,2,3,4,5,6], "raw_grade":['a', 'b', 'b', 'a', 'a', 'e']})
#Recast grade as a categorical variable
df["grade"] = df["raw_grade"].astype("category")

df["grade"]

#Gives this:
Out[124]: 
0    a
1    b
2    b
3    a
4    a
5    e
Name: grade, dtype: category
Categories (3, object): [a, b, e]

You can also rename categories and add missing categories

Answer 2

You could have a separate dictionary which maps values to labels:

 d={0:"no rain",1:"raining"}

and then you could access the labelled data by doing

 df.rain_column.apply(lambda x:d[x])