Pearson_correlation.ipynb

Kernel: Python 3 (Anaconda)

import numpy as np
import scipy as sp
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline

data = pd.read_csv('longley.csv', header=0, index_col=0)
data.info()

<class 'pandas.core.frame.DataFrame'>
Int64Index: 16 entries, 1947 to 1962
Data columns (total 7 columns):
GNP.deflator    16 non-null float64
GNP             16 non-null float64
Unemployed      16 non-null float64
Armed.Forces    16 non-null float64
Population      16 non-null float64
Year            16 non-null int64
Employed        16 non-null float64
dtypes: float64(6), int64(1)
memory usage: 1.0 KB

data.head(5)

data['Employed'].corr(data['Population'], method='pearson')

0.96039057159437557