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数据科学 教程

如今,数据主宰着世界。这导致了对数据科学家的巨大需求。

数据科学家帮助公司做出数据驱动的决策,以改善其业务。

现在就开始学习数据科学 »

通过示例学习

使用我们的“尝试一下”编辑器,您可以编辑 Python 代码并查看结果。

示例

import pandas as pd
import matplotlib.pyplot as plt
from scipy import stats

full_health_data = pd.read_csv("data.csv", header=0, sep=",")

x = full_health_data["Average_Pulse"]
y = full_health_data["Calorie_Burnage"]

slope, intercept, r, p, std_err = stats.linregress(x, y)

def myfunc(x)
 return slope * x + intercept

mymodel = list(map(myfunc, x))

plt.scatter(x, y)
plt.plot(x, mymodel)
plt.ylim(ymin=0, ymax=2000)
plt.xlim(xmin=0, xmax=200)
plt.xlabel("Average_Pulse")
plt.ylabel ("Calorie_Burnage")
plt.show()
尝试一下 »

点击“尝试一下”按钮查看其工作原理。


Python 语言

Python 是一种被数据科学家广泛使用的编程语言。

Python 内置了数学库和函数,使得计算数学问题和执行数据分析变得更容易。

在本教程中,我们将使用 Python 提供实际示例。

要了解有关 Python 的更多信息,请访问我们的 Python 教程


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