1 折线图
import pandas
import matplotlib.pylab as plt
sentiment = pandas.read_csv('sentiment.csv')
print(sentiment.columns)
sentiment['DATE'] = pandas.to_datetime(sentiment['DATE']) #转为标准时间模式
print(sentiment.head(5))
first_12 = sentiment[0:12]
plt.plot(first_12['DATE'],first_12['UMCSENT']) #绘制折线图
plt.xticks(rotation=45) #x轴斜着写
plt.xlabel('month') #x标签
plt.ylabel('sentiment') #y标签
plt.title('Monthly Sentiment Trend,2000') #标题
plt.show() #图片显示
输出：
Index(['DATE', 'UMCSENT'], dtype='object')
DATE UMCSENT
0 2000-01-01 112.0
1 2000-02-01 111.3
2 2000-03-01 107.1
3 2000-04-01 109.2
4 2000-05-01 110.7
Figure_1.png
2 子图设置
2.1 add_subplot()
import matplotlib.pylab as plt
import numpy
fig = plt.figure(figsize=(6,6)) #画图域
ax1 = fig.add_subplot(2,3,1)
ax2 = fig.add_subplot(2,3,2)
ax3 = fig.add_subplot(2,3,6)
ax1.plot(numpy.random.randint(1,5,5),numpy.arange(5))
ax2.plot(numpy.arange(10)*3,numpy.arange(10))
plt.show()
输出：
Figure_2.png
2.2 同张图画两条
import pandas
sentiment = pandas.read_csv('sentiment.csv')
print(sentiment.columns)
sentiment['DATE'] = pandas.to_datetime(sentiment['DATE'])
sentiment['MONTH'] = sentiment['DATE'].dt.month #取月份
sentiment['MONTH'] = sentiment['DATE'].dt.month
fig = plt.figure(figsize=(12,6))
plt.plot(sentiment[0:12]['MONTH'],sentiment[0:12]['UMCSENT'],c='red')
plt.plot(sentiment[12:24]['MONTH'],sentiment[12:24]['UMCSENT'],c='blue')
plt.xticks(rotation=45)
plt.xlabel('month')
plt.show()
输出：
Figure_3.png
2.3 用for循环画图，并设置标签
import matplotlib.pylab as plt
import pandas
sentiment = pandas.read_csv('sentiment.csv')
sentiment['DATE'] = pandas.to_datetime(sentiment['DATE'])
fig = plt.figure(figsize=(12,6))
colours = ['red','blue','green','orange','pink']
for i in range(5):
star_index = i*12
end_index = (i+1)*12
y_i = sentiment[star_index:end_index]
label = str(2000+i)
plt.plot(y_i['DATE'].dt.month,y_i['UMCSENT'],c=colours[i],linewidth = 3,label=label)#linewidth指定粗细
# plt.text(12,90,'2003') #添加文字到图上
plt.legend(loc=0) #加标签 1-右上角，2-左上角，3-左下角，4-右下角，0-最合适的位置
# print(help(plt.legend))
plt.show()
输出：
Figure_4.png
3 柱状图和条形图
import pandas
import matplotlib.pylab as plt
from numpy import arange
nba_2013 = pandas.read_csv('nba_2013.csv')
print(nba_2013.columns)
num_columns = ['age','g','gs','fg','fga']
bar_hights = nba_2013.ix[0,num_columns].values
print(bar_hights)
bar_positions = arange(5)+0.75
print(bar_positions)
#柱状图
ax=plt.subplot(121)
ax.bar(bar_positions,bar_hights,0.3) #0.3：柱的宽度 bar柱形图
ax.set_xlabel('x')
ax.set_ylabel('y')
ax.set_xticklabels(num_columns)
#条形图
ax2=plt.subplot(122)
ax2.barh(bar_positions,bar_hights,0.3) #0.3：柱的宽度 barh条形图
ax2.set_xlabel('x')
ax2.set_ylabel('y')
ax2.set_xticklabels(num_columns)
plt.show()
输出：
Index(['player', 'pos', 'age', 'bref_team_id', 'g', 'gs', 'mp', 'fg', 'fga',
'fg.', 'x3p', 'x3pa', 'x3p.', 'x2p', 'x2pa', 'x2p.', 'efg.', 'ft',
'fta', 'ft.', 'orb', 'drb', 'trb', 'ast', 'stl', 'blk', 'tov', 'pf',
'pts', 'season', 'season_end'],
dtype='object')
[23 63 0 66 141]
[0.75 1.75 2.75 3.75 4.75]
Figure_5.png
4 散点图
ax = plt.subplot()
ax.scatter(nba_2013['age'],nba_2013['g'])
ax.set_xlabel('age')
ax.set_ylabel('g')
plt.show()
输出：
Figure_6.png
5 直方图
import pandas as pd
import matplotlib.pylab as plt
nba_2013 = pd.read_csv('nba_2013.csv')
cols = ['age','g','gs','fg','fga']
nba = nba_2013[cols]
print(nba[:5])
Age = nba['age'].value_counts() #计算相同年龄的个数
Age = Age.sort_index()
G = nba['g'].value_counts()
G = G.sort_index()
print('----------------')
print(Age)
print('-------------------')
print(G)
ax = plt.subplot()
ax.hist(nba_2013['age'],bins=20) #20个柱形
ax.ylim(0.90) #设置y轴区间
plt.show()
输出：
age g gs fg fga
0 23 63 0 66 141
1 20 81 20 93 185
2 27 53 12 143 275
3 28 73 73 464 1011
4 25 56 30 136 249
----------------
19 2
20 16
21 23
22 41
23 50
24 45
25 51
26 43
27 39
28 36
29 29
30 17
31 21
32 14
33 20
34 8
35 10
36 6
37 6
38 2
39 2
Name: age, dtype: int64
-------------------
1 2
2 11
3 6
4 2
5 6
6 5
7 2
8 4
9 3
10 1
11 5
12 1
13 3
14 4
15 5
17 1
18 1
19 3
20 6
21 5
22 8
23 5
24 6
25 2
26 5
27 2
28 2
29 4
30 3
31 7
..
54 8
55 8
56 4
57 1
58 5
59 4
60 6
61 6
62 7
63 8
64 7
65 7
66 4
67 5
68 9
69 7
70 9
71 9
72 13
73 18
74 8
75 3
76 10
77 14
78 12
79 14
80 23
81 22
82 28
83 1
Name: g, Length: 82, dtype: int64
Figure_7.png
6 箱线图
6.1 一个
nba_2013 = pd.read_csv('nba_2013.csv')
ax = plt.subplot()
ax.boxplot(nba_2013['age']) #.values 也行
ax.set_xticklabels(['age'])
plt.show()
输出：
Figure_8.png
6.2 多个
nba_2013 = pd.read_csv('nba_2013.csv')
nba_col = ['age','g','gs','fg','fga']
nba = nba_2013[nba_col]
ax = plt.subplot()
ax.boxplot(nba.values)
ax.set_xticklabels(nba_col,rotation=45)
plt.show()
输出：
Figure_9.png
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