pythonplt画图使⽤csv数据⽂件在
import pandas as pd
unrate = pd.read_csv('unrate.csv')
# pd.to_datetime() 转换成⽇期格式，即由 1948/1/1 转换为 1948-01-01
unrate['DATE']= pd.to_datetime(unrate['DATE'])
print(unrate.head(12))
DATE  VALUE
01948-01-01  3.4
11948-02-01  3.8
21948-03-01  4.0
31948-04-01  3.9
41948-05-01  3.5
51948-06-01  3.6
61948-07-01  3.6
71948-08-01  3.9
81948-09-01  3.8
91948-10-01  3.7
101948-11-01  3.8
111948-12-01  4.0
⾸先导⼊plt库
import matplotlib.pyplot as plt
折线图
first_twelve = unrate[0:12]
plt.plot(first_twelve['DATE'], first_twelve['VALUE'])
plt.show()
可以看出横坐标太长，我们可以旋转⼀下横坐标
plt.plot(first_twelve['DATE'], first_twelve['VALUE'])
plt.xlabel('Month')
plt.ylabel('Unemployment Rate')
plt.title('Monthly Unemployment Trends, 1948')
plt.show()
plt可以画多个⼦图
import numpy as np
fig = plt.figure()
ax1 = fig.add_subplot(2,1,1)# 画2⾏1列个图形的第1个
ax2 = fig.add_subplot(2,1,2)# 画2⾏1列个图形的第2个
ax1.plot(np.random.randint(1,5,5), np.arange(5))
ax2.plot(np.arange(10)*3, np.arange(10))
plt.show()
可以设置图⼤⼩，添加图例
unrate['MONTH']= unrate['DATE'].dt.month
unrate['MONTH']= unrate['DATE'].dt.month
fig = plt.figure(figsize=(6,3))# 设置图⼤⼩ figsize=(6,3)
plt.plot(unrate[0:12]['MONTH'], unrate[0:12]['VALUE'], c='red',label ='0-12 months') plt.plot(unrate[12:24]['MONTH'], unrate[12:24]['VALUE'], c='blue',label ='12-24 months') plt.legend(loc='best')
plt.show()
柱形图
reviews = pd.read_csv('fandango_scores.csv')
cols =['FILM','RT_user_norm','Metacritic_user_nom','IMDB_norm','Fandango_Ratingvalue','Fandango_Stars'] norm_reviews = reviews[cols]
print norm_reviews.shape
(146,6)
import matplotlib.pyplot as plt
from numpy import arange
num_cols =['RT_user_norm','Metacritic_user_nom','IMDB_norm','Fandango_Ratingvalue','Fandango_Stars'] bar_heights = norm_reviews.ix[0, num_cols].values
bar_positions = arange(5)+0.75
tick_positions =range(1,6)
fig, ax = plt.subplots()
ax.bar(bar_positions, bar_heights,0.5)#画柱形图，0.5表⽰柱的宽度，，ax.barh画⽔平的柱形图
ax.set_xticks(tick_positions)
ax.set_xticklabels(num_cols, rotation=45)
ax.set_xlabel('Rating Source')
ax.set_ylabel('Average Rating')
ax.set_title('Average User Rating For Avengers: Age of Ultron (2015)')
python新手代码画图
plt.show()
散点图
fig, ax = plt.subplots()
ax.scatter(norm_reviews['Fandango_Ratingvalue'], norm_reviews['RT_user_norm'])#画散点图
ax.set_xlabel('Fandango')
ax.set_ylabel('Rotten Tomatoes')
plt.show()
统计bins柱形图
import matplotlib.pyplot as plt
reviews = pd.read_csv('fandango_scores.csv')
cols =['FILM','RT_user_norm','Metacritic_user_nom','IMDB_norm','Fandango_Ratingvalue'] norm_reviews = reviews[cols]
fandango_distribution = norm_reviews['Fandango_Ratingvalue'].value_counts()
fandango_distribution = fandango_distribution.sort_index()
print(fandango_distribution)
2.72
2.82
2.95
3.04
3.13
3.25
3.34
3.49
3.59
3.68
3.79
3.85
3.912
4.07
4.116
4.212
4.311
4.47
4.59
4.64
4.83
Name: Fandango_Ratingvalue, dtype: int64
fig, ax = plt.subplots()
# 分成20个bins，统计4-5的数据
ax.hist(norm_reviews['Fandango_Ratingvalue'],range=(4,5),bins=20)
plt.show()
箱形图
num_cols =['RT_user_norm','Metacritic_user_nom','IMDB_norm','Fandango_Ratingvalue'] fig, ax = plt.subplots()
ax.boxplot(norm_reviews[num_cols].values)# boxplot 画箱形图 .values转换成array形式
ax.set_xticklabels(num_cols, rotation=90)
ax.set_ylim(0,5)
plt.show()
设置边框样式
import pandas as pd
import matplotlib.pyplot as plt
women_degrees = pd.read_csv('percent-bachelors-degrees-women-usa.csv')
fig, ax = plt.subplots()
ax.plot(women_degrees['Year'], women_degrees['Biology'], c='blue', label='Women') ax.plot(women_degrees['Year'],100-women_degrees['Biology'], c='green', label='Men') ax.tick_params(bottom="on", top="on", left="off", right="off")#将左右的⼩横杆去掉
for key,spine in ax.spines.items():#设置边框不可见
spine.set_visible(False)
# End solution code.
ax.legend(loc='upper right')
plt.show()
设置线颜⾊，粗细

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