Seaborn-03-数据分布图

发表于 2017-02-15 | 分类于 Python |

基本

#-*- coding:utf-8 -*-
from __future__ import division
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy import stats, integrate
import seaborn as sns

1、快速查看分布

distplot

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x = np.random.randint(0,10,100)
sns.distplot(x, color="b", bins=10, rug=True)
sns.distplot(x, hist=False)

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Seaborn-02-颜色板控制

发表于 2017-02-15 | 分类于 Python |

基本

#-*- coding:utf-8 -*-
from __future__ import division
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

1、定性调色板 Qualitative

默认的定性调色板：deep, muted, pastel, bright, dark, colorblind.

1 2	current_palette = sns.color_palette() sns.palplot(current_palette)

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Seaborn-01-图控制

发表于 2017-02-15 | 分类于 Python |

基本

#-*- coding:utf-8 -*-
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt

1、引入 seaborn 风格

def sinplot(flip=1):
    x = np.linspace(0, 14, 100)
    for i in range(1, 7):
        plt.plot(x, np.sin(x + i * .5) * (7 - i) * flip)
sinplot()

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Pandas-office-10分钟开始

发表于 2017-02-15 | 分类于 Python |

基本

# -*- coding:utf-8 -*-
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

1、创建数据框

dates = pd.date_range('20130101', periods=6)
df = pd.DataFrame(np.random.randn(6, 4), index=dates, columns=list('ABCD'))
left = pd.DataFrame({'key': ['foo', 'foo'], 'lval': [1, 2]})
right = pd.DataFrame({'key': ['foo', 'foo'], 'rval': [4, 5]})

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