通過軸排序
import pandas as pd
import numpy as np
dates=pd.date_range('20190301`,periods=6)
df = pd.dataframe(np.random.randn(6,4),index=dates,columns=list('abcd'))
print(df.sort_index(axis=1,ascending=false)
d c b a
2019-03-01 -0.791684 -0.487994 0.609415 -0.130605
2019-03-02 -1.547686 0.424872 0.774110 -0.444310
2019-03-03 0.017846 1.498144 -0.384752 -2.453477
2019-03-04 0.727243 -0.112879 1.297718 0.278707
2019-03-05 0.506601 0.796999 1.532483 -1.643227
2019-03-06 -0.217591 -2.295332 -1.521089 -0.051233
按b軸排序
print(df.sort_values(by='b'))a b c d
2019-03-06 -0.051233 -1.521089 -2.295332 -0.217591
2019-03-03 -2.453477 -0.384752 1.498144 0.017846
2019-03-01 -0.130605 0.609415 -0.487994 -0.791684
2019-03-02 -0.444310 0.774110 0.424872 -1.547686
2019-03-04 0.278707 1.297718 -0.112879 0.727243
2019-03-05 -1.643227 1.532483 0.796999 0.506601
逆序排print(df.sort_values(by='b',ascending=false))
pandas取數獲取
選擇一列，產生乙個系列，相當於df.a
print(df['a'])2019-03-01 -0.130605
2019-03-02 -0.444310
2019-03-03 -2.453477
2019-03-04 0.278707
2019-03-05 -1.643227
2019-03-06 -0.051233
freq: d, name: a, dtype: float64
通過操作符選擇切片行（預設axis=0）
dates=pd.date_range('20190101',periods=6)
df=pd.dataframe(np.random.randn(6.4),index=dates,columns=list('abcd'))
df=pd.dataframe(np.random.randn(6,4),index=dates,columns=list('abcd'))
print(df[0:3])
a b c d
2019-01-01 0.856435 -1.004727 1.922469 0.137247
2019-01-02 -0.197909 1.979294 1.754650 0.900661
2019-01-03 0.298422 0.446164 -0.281074 -1.514126
print(df['20190102':'20190103'])a b c d
2019-01-02 -0.197909 1.979294 1.754650 0.900661
2019-01-03 0.298422 0.446164 -0.281074 -1.514126
按標籤選擇
使用標籤獲取橫截面
import pandas as pd
import numpy as np
dates = pd.date_range('20190101',periods=6)
df = pd.dataframe(np.random.randn(6,4),index=dates,columns=list('abcd'))
print(df.loc[dates[0]])
a 1.755160
b 1.889182
c 1.646745
d 0.418026
name: 2019-01-01 00:00:00, dtype: float64
print(df.loc[:,['a','b']])a b2019-01-01 1.755160 1.889182
2019-01-02 -1.687622 1.189862
2019-01-03 0.242299 -0.810373
2019-01-04 -0.758775 0.855404
2019-01-05 -0.316525 -1.058533
2019-01-06 1.584005 1.586659
print(df.loc['20190102':'20190104',['a','c']])a c2019-01-02 -1.687622 0.565117
2019-01-03 0.242299 0.703034
2019-01-04 -0.758775 0.297482
print(df.loc['20190102',['a','b']])a -1.687622
b 1.189862
name: 2019-01-02 00:00:00, dtype: float64
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