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Python机器学习手册:从数据预处理到深度学习
book

Python机器学习手册:从数据预处理到深度学习

by Chris Albon
July 2019
Intermediate to advanced
365 pages
8h 13m
Chinese
Publishing House of Electronics Industry
Content preview from Python机器学习手册:从数据预处理到深度学习
3.7
 计算最小值、最大值、总和、平均值与计数值
43
3.7
 计算最小值、最大值、总和、平均值与计数值
问题描述
计算一个数值列的最小值、最大值、总和、平均值与计数值。
解决方案
pandas
提供了一些内置的方法来计算常见的描述性统计量
#
加载库
import pandas as pd
#
创建
URL
url = 'https://tinyurl.com/titanic-csv'
#
加载数据
dataframe = pd.read_csv(url)
#
计算描述统计量
print('Maximum:', dataframe['Age'].max())
print('Minimum:', dataframe['Age'].min())
print('Mean:', dataframe['Age'].mean())
print('Sum:', dataframe['Age'].sum())
print('Count:', dataframe['Age'].count())
Maximum: 71.0
Minimum: 0.17
Mean: 30.397989417989415
Sum: 22980.879999999997
Count: 756
讨论
除了解决方案中用到的描述性统计量,
pandas
还提供了计算方差(
var
)、标准差(
std
)、
峰态(
kurt
)、偏态(
skew
)、平均值标准误差(
sem
)、众数(
mode
)、中位数(
median
以及很多其他描述性统计量的方法。 ...
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Publisher Resources

ISBN: 9787121369629