import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.randn(20, 5))
df.columns = ['score_1', 'score_2', 'score_3', 'score_4', 'score_5']
df
score_1 | score_2 | score_3 | score_4 | score_5 | |
---|---|---|---|---|---|
0 | 0.809013 | -0.043927 | 0.928440 | -1.110457 | 1.623501 |
1 | 1.626228 | -0.304158 | 1.249759 | -1.851839 | 1.081616 |
2 | 1.894077 | 1.068677 | -0.111965 | -1.064986 | 0.035659 |
3 | -0.386469 | -1.188364 | 0.831405 | -0.014511 | -0.260195 |
4 | -1.242064 | 0.294049 | 0.714657 | -0.396795 | -1.219513 |
5 | 0.852891 | 0.355283 | 0.839451 | 0.746963 | -0.715827 |
6 | 0.191754 | -0.244156 | -0.238739 | 0.797857 | -1.355429 |
7 | 0.175954 | -0.465887 | 1.882503 | -0.174788 | 0.646117 |
8 | -0.404646 | -0.755381 | 0.419163 | 0.918593 | 0.923306 |
9 | -0.108578 | 0.166226 | 0.890846 | -0.016745 | -1.375534 |
10 | 0.101022 | -0.132286 | 0.274950 | -0.678942 | 0.053938 |
11 | 1.673355 | -0.164933 | 1.086568 | -1.621484 | -0.135308 |
12 | 1.128543 | 0.355407 | -1.380984 | 0.604208 | -1.095205 |
13 | -1.602945 | 0.614549 | -0.089838 | 0.652979 | 1.721376 |
14 | -1.272730 | -0.916772 | -0.594153 | 0.123623 | -0.655120 |
15 | 0.140682 | -0.364991 | -0.522412 | 0.863911 | 1.106638 |
16 | -0.265389 | -0.293563 | 1.066478 | -0.485762 | -2.222239 |
17 | 2.465491 | -0.437448 | -1.577115 | 0.243174 | -0.186260 |
18 | 0.927383 | -0.615659 | -0.075537 | 0.939576 | -0.662184 |
19 | -0.426472 | 0.990325 | 0.314062 | -0.678511 | 0.570545 |
20 rows × 5 columns
df.describe()
score_1 | score_2 | score_3 | score_4 | score_5 | |
---|---|---|---|---|---|
count | 20.000000 | 20.000000 | 20.000000 | 20.000000 | 20.000000 |
mean | 0.313855 | -0.104151 | 0.295377 | -0.110197 | -0.106006 |
std | 1.101752 | 0.592899 | 0.879432 | 0.860297 | 1.081506 |
min | -1.602945 | -1.188364 | -1.577115 | -1.851839 | -2.222239 |
25% | -0.391013 | -0.444558 | -0.143658 | -0.678619 | -0.810672 |
50% | 0.158318 | -0.204545 | 0.366613 | -0.015628 | -0.160784 |
75% | 0.977673 | 0.309358 | 0.900244 | 0.676475 | 0.715414 |
max | 2.465491 | 1.068677 | 1.882503 | 0.939576 | 1.721376 |
8 rows × 5 columns
col = df['score_1']
col[np.abs(col) > 2]