[PYTHON] Seaborn basics for beginners ② Histogram (distplot)

What is seaborn

A library for drawing Python graphs. .. Positioned as a wrapper function (inclusive program) of matplotlib, the most famous libra. In addition to being able to easily draw beautiful-looking graphs, it also has a certain amount of functions such as batch processing. Matplotlib is for detailed specification and drawing, and seaborn is for easy and beautiful.

Histogram (distplot)

The theme this time is a histogram. Use distplot to create the histogram. Please compare the difference in appearance and parameters with the following article using "matplotlib". ★ Create histogram with pandas basic matplotlib for beginners

Preparation

First, install the seaborn library with pip. For pip ?, click here ('https://qiita.com/Yanagawa_Yoshihisa/items/35e6f70a8411277282ce').

Import the library. Name seaborn`` sns and ʻimport`.

python

import seaborn as sns

I will try the sample with Titanic data. If you don't know Titanic, please check "kaggle Titanic". Create a dataframe with pandas.

python

dataframe = pd.read_csv('train.csv')

Basic creation

Use distplot to create the histogram. As an example, create a histogram by Age. In kde, whether or not to draw the density approximation function. It's difficult, so set it like a spell. Setting rug to True normalizes the Y-axis sum to 1. It's difficult, so set it like a spell.

python

sns.distplot(dataframe['Age'],kde=False, rug=False)

bins settings

Use bins to set the number of bars. Set 10 as an example.

python

sns.distplot(dataframe['Age'],bins = 10,kde=False, rug=False)

How many bins should I have? If you have any doubts, check out the Starges formula.

(Application) Overlapping multiple

It may not be very useful, but to stack it, you only have to write the syntax twice. Let's divide by Sex. Divide the data as a preparation.

python

malelist_m = dataframe['Sex'] == 'male'
malelist_f = dataframe['Sex'] == 'female'

Write the syntax continuously.

python

sns.distplot(dataframe[malelist_m]['Age'],bins = 10,kde=False, rug=False )
sns.distplot(dataframe[malelist_f]['Age'],bins = 10,kde=False, rug=False )

If you want to use labels etc., you need to use the function of "matplotlib". that's all.

Finally

As a beginner can understand, we have summarized the necessary knowledge when implementing machine learning with Python as a simple article. The table of contents is here, so I hope you can refer to other articles as well.