Correlation between two non-numeric columns in a Pandas DataFrame

Question

I get my data from a SQL query from the table to my pandas Dataframe. The data looks like:

     group phone_brand
0      M32-38          小米
1      M32-38          小米
2      M32-38          小米
3      M29-31          小米
4      M29-31          小米
5      F24-26        OPPO
6      M32-38          酷派
7      M32-38          小米
8      M32-38        vivo
9      F33-42          三星
10     M29-31          华为
11     F33-42          华为
12     F27-28          三星
13     M32-38          华为
14       M39+         艾优尼
15     F27-28          华为
16     M32-38          小米
17     M32-38          小米
18       M39+          魅族
19     M32-38          小米
20     F33-42          三星
21     M23-26          小米
22     M23-26          华为
23     M27-28          三星
24     M29-31          小米
25     M32-38          三星
26     M32-38          三星
27     F33-42          三星
28     M32-38          三星
29     M32-38          三星
...       ...         ...
74809  M27-28          华为
74810  M29-31         TCL

Now I want to found the correlation and the frequency from this to columns. But this in a visualization with Matplotlib. I try something like:

DataFrame.plot(style='o')
plt.show() 

Now how can I visualize this correlation at simplest way?

Answer 1

To quickly get a correlation:

df.apply(lambda x: x.factorize()[0]).corr()

                group  phone_brand
group        1.000000     0.427941
phone_brand  0.427941     1.000000

---

Heat map

import seaborn as sns

sns.heatmap(pd.crosstab(df.group, df.phone_brand))