已信任
Jupyter 服务器: 本地
Python 3: Not Started
[60]
import pandas as pd
import numpy as np
[61]
s = pd.Series([877,865,874,890,912])
s
0 877
1 865
2 874
3 890
4 912
dtype: int64
[62]
# 想知道每天的变化量,对比的是当天跟昨天的变化量
s.pct_change()
0 NaN
1 -0.013683
2 0.010405
3 0.018307
4 0.024719
dtype: float64
[63]
# 协方差
s1 = pd.Series(np.random.randn(10))
s2 = pd.Series(np.random.randn(10))
s1.cov(s2)
-0.3417718431113297
[64]
# 相关性计算:一个变，另一个是否跟着变
s1
0 0.070405
1 0.155567
2 -0.518001
3 -0.057693
4 0.411682
5 1.841240
6 0.759474
7 0.301355
8 -0.864013
9 0.642086
dtype: float64
[65]
s2 = s1*2
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s1.corr(s2)
1.0
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s3 = pd.Series(np.random.randn(10))
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df = pd.DataFrame({
's1':s1,
's2':s2,
's3':s3
})
df
s1 s2 s3
0 0.070405 0.140811 0.771643
1 0.155567 0.311135 2.976528
2 -0.518001 -1.036002 -0.368043
3 -0.057693 -0.115387 0.273931
4 0.411682 0.823364 0.434022
5 1.841240 3.682480 -1.641432
6 0.759474 1.518949 0.682910
7 0.301355 0.602710 0.514268
8 -0.864013 -1.728025 0.023511
9 0.642086 1.284171 0.960029
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df.corr()
s1 s2 s3
s1 1.000000 1.000000 -0.278755
s2 1.000000 1.000000 -0.278755
s3 -0.278755 -0.278755 1.000000
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