Seaborn数据可视化入门

在本节学习中，我们使用Seaborn作为数据可视化的入门工具

Seaborn的官方网址如下：http://seaborn.pydata.org

一：definition

Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics.

Seaborn是基于matplotlib的数据可视化库，它的主要功能是做数据可视化

二：Setup the notebook

对数据进行初始化，引入相应的包

import pandas as pd

import matplotlib.pyplot as plt

%matplotlib inline

import seaborn as sns

pirnt("Setup Complete")

三: Load the data

加载数据

file_path = "../input/fifa.csv"

fifa_data = pd.read_csv(file_path, index_col="Date", parse_Dates=True)

注：

file_path:

表示dataset的路径

idnex_col="Date" :

When we load the dataset, we want each entry in the first column to denote a different row. To do this, we set the value of index_col to the name of the first column ("Date", found in cell A1 of the file when it's opened in Excel).

parse_dates=True：

This tells the notebook to understand the each row label as a date (as opposed to a number or other text with a different meaning).

四: Examine the data

列出数据的前5行检验：

fifa_data.head()

五: Plot the data

Line Chart

　　plt.figure(figsize=(16,6))

　　sns.lineplot(data=fifa_data)

注：

plt.figure(figsize=(16,6))

设定的是图形的宽度和高度

plt.title("name") 增加title，并命名为name

sns.lineplot(data=fifa_data)画出数据的线状图

若想plot a subset of the data （仅仅画出一部分图线）：

sns.lineplot(data=spotify["shape of you"],label=shape of you")

sns.lineplot(data=spotify["despacito"], label="despatito")

plt.xlabel("name X")

plt.blabel("name Y")

注：

plt.xlabel

plt.ylabel

是分别对label x, y 进行命名

Bar Charts

　　plt.title("Average Arrival Delay for Spirit Airlines Flights, by Month")

　　sns.barplot(x=flight_data.index, y=flight_data['NK'])

　　plt.ylabel("Arrival delay (in minutes)"

注：

x=flight_data.index ：

This determines what to use on the horizontal axis. In this case, we have selected the column that indexes the rows (in this case, the column containing the months).