集中趨勢

Python 統計學入門

Maggie Matsui

Content Developer, DataCamp

哺乳類睡眠資料

print(msleep)

                 name       genus   vore         order  ... sleep_cycle  awake  brainwt   bodywt
1             Cheetah    Acinonyx  carni     Carnivora  ...         NaN   11.9      NaN   50.000
2          Owl monkey       Aotus   omni      Primates  ...         NaN    7.0  0.01550    0.480
3     Mountain beaver  Aplodontia  herbi      Rodentia  ...         NaN    9.6      NaN    1.350
4 Greater short-ta...     Blarina   omni  Soricomorpha  ...    0.133333    9.1  0.00029    0.019
5                 Cow         Bos  herbi  Artiodactyla  ...    0.666667   20.0  0.42300  600.000
..                ...         ...    ...           ...  ...         ...    ...      ...      ...
79         Tree shrew      Tupaia   omni    Scandentia  ...    0.233333   15.1  0.00250    0.104
80 Bottle-nosed do...    Tursiops  carni       Cetacea  ...         NaN   18.8      NaN  173.330
81              Genet     Genetta  carni     Carnivora  ...         NaN   17.7  0.01750    2.000
82         Arctic fox      Vulpes  carni     Carnivora  ...         NaN   11.5  0.04450    3.380
83            Red fox      Vulpes  carni     Carnivora  ...    0.350000   14.2  0.05040    4.230

直方圖

這個資料集的哺乳類通常睡多久？

什麼是典型值？

資料的中心在哪裡？

平均數
中位數
眾數

Screen Shot 2020-07-02 at 11.01.16 AM.png

集中趨勢：平均數

                  name  sleep_total
1              Cheetah         12.1
2           Owl monkey         17.0
3      Mountain beaver         14.4
4   Greater short-t...         14.9
5                  Cow          4.0
..                 ...          ...

$\text{Mean sleep time}=$

$$\frac{12.1 + 17.0 + 14.4 + 14.9 + ...}{83} = 10.43$$

import numpy as np
np.mean(msleep['sleep_total'])

10.43373

集中趨勢：中位數

msleep['sleep_total'].sort_values()

msleep['sleep_total'].sort_values().iloc[41]

10.1

np.median(msleep['sleep_total'])

10.1

集中趨勢：眾數

最常見的值

msleep['sleep_total'].value_counts()

12.5    4
10.1    3
14.9    2
11.0    2
8.4     2
...
14.3    1
17.0    1
Name: sleep_total, Length: 65, dtype: int64

msleep['vore'].value_counts()

herbi      32
omni       20
carni      19
insecti     5
Name: vore, dtype: int64

import statistics
statistics.mode(msleep['vore'])

'herbi'

加入離群值

# Subset msleep to select rows where 'vore' equals 'insecti'
msleep[msleep['vore'] == 'insecti']

                     name         genus     vore         order  sleep_total
22          Big brown bat     Eptesicus  insecti    Chiroptera         19.7
43       Little brown bat        Myotis  insecti    Chiroptera         19.9
62        Giant armadillo    Priodontes  insecti     Cingulata         18.1
67  Eastern american mole      Scalopus  insecti  Soricomorpha          8.4

加入離群值

msleep[msleep['vore'] == "insecti"]['sleep_total'].agg(["mean", "median"])

mean      16.53
median    18.9
Name: sleep_total, dtype: float64

加入離群值

msleep[msleep['vore'] == 'insecti']

                     name         genus     vore         order  sleep_total
22          Big brown bat     Eptesicus  insecti    Chiroptera         19.7
43       Little brown bat        Myotis  insecti    Chiroptera         19.9
62        Giant armadillo    Priodontes  insecti     Cingulata         18.1
67  Eastern american mole      Scalopus  insecti  Soricomorpha          8.4

84    Mystery insectivore            ... insecti           ...          0.0

加入離群值

msleep[msleep['vore'] == "insecti"]['sleep_total'].agg(["mean", "median"])

mean      13.22
median    18.1
Name: sleep_total, dtype: float64

平均數： 16.5 → 13.2

中位數： 18.9 → 18.1

該用哪一種指標？

# Import matplotlib.pyplot with alias plt
import matplotlib.pyplot as plt

# Histogram of values
data['values'].hist()

# Show the plot
plt.show()

symmetrical data histogram

偏態

左偏

Histogram of data with few values on the left, increasing to more values on the right.

右偏

Histogram of data with many values on the left, decreasing to few values on the right.

該用哪一種指標？

Histogram of data with few values on the left, increasing to more values on the right.

Histogram of data with many values on the left, decreasing to few values on the right.

一起來練習吧！

Python 統計學入門