Python数据分析之可视化一matplotlib(常用方法)

data = sns.load_dataset("iris")
data.head()
# 萼片长度，萼片宽度，花瓣长度，花瓣宽度，种类

# your code
%matplotlib inline
import matplotlib
from matplotlib import pyplot as plt
import seaborn as sns
import pandas as pd

data.loc[:,'sepal'] = data['sepal_length'] * data['sepal_width']
data.loc[:,'petal'] = data['petal_length'] * data['petal_width']
plt.scatter(data['sepal'],data['petal'])
plt.title('the relation of the sepal and the petal ')

for i in list(data['species'].unique()):
plt.scatter(data['sepal'],data['petal'],c=['b','g','r'])
plt.title('the relation of the sepal and the petal ')


第二个小例子data = sns.load_dataset("tips")
data.head()
# 总消费，小费，性别，吸烟与否，就餐星期，就餐时间，就餐人数

sex = data['sex'].unique()
tip = []

for i in sex:
tip.append(data[data['sex'] == i]['tip'].values)
tip
#plt.boxplot(female_tip)

fig, ax = plt.subplots()
ax.boxplot(tip)
ax.set_xticklabels(sex)
ax.set_title('the tip of sex')

days = data['day'].unique()
tip = []
for day in days:
tip.append(data[data['day'] == day]['tip'].values)

def boxplot(x_data, y_data, base_color, median_color, x_label, y_label, title):
_, ax = plt.subplots()

# 设置样式
ax.boxplot(y_data
# 箱子是否颜色填充
, patch_artist = True
# 中位数线颜色
, medianprops = {'color': base_color}
# 箱子颜色设置，color：边框颜色，facecolor：填充颜色
, boxprops = {'color': base_color, 'facecolor': median_color}
# 猫须颜色whisker
, whiskerprops = {'color': median_color}
# 猫须界限颜色whisker cap
, capprops = {'color': base_color})

# 箱图与x_data保持一致
ax.set_xticklabels(x_data)
ax.set_ylabel(y_label)
ax.set_xlabel(x_label)
ax.set_title(title)

# 调用绘图函数
boxplot(x_data = days
, y_data = tip
, base_color = 'b'
, median_color = 'g'
, x_label = 'Day of week'
, y_label = 'tips'
, title = 'The tip of day')


想成为可视化高手，请戳 https://matplotlib.org/api/pyplot_api.html