# Category x Quantity のPlot

titanic_plot.py

```python3
# https://github.com/PyDataTokyo/pydata-tokyo-tutorial-1/blob/master/pydatatokyo_tutorial_ml.ipynb

# のロジスティック回帰による生存者推定 plot をseabornを使って簡潔にやってみた
# 今回以外にもcategoryデータを利用するplotの例があってよかった

# https://stanford.edu/~mwaskom/software/seaborn/generated/seaborn.swarmplot.html
# https://stanford.edu/~mwaskom/software/seaborn/generated/seaborn.stripplot.html
%matplotlib inline

import pandas as pd
import seaborn as sns

titanic = sns.load_dataset("titanic")
_titanic = pd.DataFrame(
    [
        titanic.age.fillna(titanic.age.mean()),
        titanic.pclass + titanic.sex.map({'female': 0, 'male': 1}).astype(int),
        titanic.survived
    ]).T
_titanic["Unnamed 0"] = _titanic["Unnamed 0"].astype("category")


#sns.swarmplot(
sns.stripplot(jitter=0.3,
    data=_titanic, x="age", y="Unnamed 0", hue="survived",
    alpha=0.3, palette=["red", "blue"])
plt.legend(bbox_to_anchor=(1.4, 1.03))
plt.tight_layout()
```
![graph.png](category_quantity_plot.png)