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viscormatrix.py
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viscormatrix.py
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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Mar 2 10:13:29 2023
@author: michele
"""
import os
import pandas as pd
import scipy.stats
import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np
os.chdir('X')
wd = 'X'
data = wd + '/cdatrans.csv'
# load in table, set index
data = pd.read_csv(data, sep = ";", decimal = ",")
data.set_index('code', inplace=True)
display(data)
# creatle triangle mask to mask out the 'double' data
low_tri = np.triu(np.ones_like(data.corr(method = 'spearman'))).astype(bool)
fig, ax = plt.subplots(figsize=(15,10))
# one
ax =sns.heatmap(data.corr(method = 'spearman'),
annot=True,
fmt=".2f", # show 2 decimal places
vmin=-1,
vmax=1,
cmap = 'coolwarm',
mask = low_tri,
cbar = True,
linecolor='white',
linewidths=1.5,
square=True,
xticklabels=True,
annot_kws={'size':12, 'weight': 'bold', 'color': 'white'})
ax.plot([0,12,0,0],[0,12,12,0],clip_on=False, color='black', lw=2)
# set xticks for better axis display
ax.set_xticklabels(ax.get_xticklabels(), rotation=22, ha='right', rotation_mode='anchor', wrap=True)
ax.set_yticklabels(ax.get_yticklabels(),wrap=True)
# title
ax.set_title("Spearman rank correlation for community interview results\n and district specific forest cover change",
fontsize=16)
# wrap layout
plt.tight_layout()
#save layout
plt.savefig("Corrplot_interview.png",
dpi = 600,
# specifying tight here so that legend is not cut
bbox_inches= "tight")
plt.show()
## find out results of p values and print
rho, p = scipy.stats.spearmanr(data[1:12])
# plot p values for later classification of p values
fig, ax = plt.subplots(figsize=(15,10))
ax =sns.heatmap(p,
annot=True,
fmt=".4f", # show 2 decimal places
vmin=-1,
vmax=1,
cmap = 'coolwarm',
mask = low_tri,
cbar = True,
linecolor='white',
linewidths=1.5,
square=True,
xticklabels=True,
annot_kws={'size':12, 'weight': 'bold', 'color': 'white'})
ax.plot([0,12,0,0],[0,12,12,0],clip_on=False, color='black', lw=2)
#ax.set_xticks(ax)
# wrap labels
#labels = [ '\n'.join(wrap(l,20)) for l in data.code]
ax.set_xticklabels(ax.get_xticklabels(), rotation=22, ha='right', rotation_mode='anchor', wrap=True)
ax.set_yticklabels(ax.get_yticklabels(),wrap=True)
ax.set_title("Spearman rank correlation for community interview results\n and district specific forest cover change",
fontsize=16)
#ax.text()
#ax.tick_params(left=False, bottom=False)
plt.tight_layout()
plt.show()