OECD exploratory data analysis

In [4]:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from scipy.stats import pearsonr
import matplotlib as mpl
import holoviews as hv
from holoviews import dim, opts
from scipy.stats import pearsonr

hv.extension('bokeh')


%matplotlib inline
# This enables high res graphics inline
%config InlineBackend.figure_format = 'svg'

sns.set_style('white')

sns.set_context("talk", font_scale=1, rc={"lines.linewidth": 2.0, 'lines.markersize': 5})
sns.set_style("ticks")
sns.set_style({"xtick.direction": "in","ytick.direction": "in"})

tw = 1.5
sns.set_style({"xtick.major.size": 6, "ytick.major.size": 6,
               "xtick.minor.size": 4, "ytick.minor.size": 4,
               'axes.labelsize': 24,
               'xtick.major.width': tw, 'xtick.minor.width': tw,
               'ytick.major.width': tw, 'ytick.minor.width': tw})

mpl.rc('xtick', labelsize=18) 
mpl.rc('ytick', labelsize=18)
mpl.rc('axes', linewidth=1.75)
plt.gcf().subplots_adjust(bottom=0.15)
sns.set_style({'axes.labelsize': 24})