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visualize correlation matrix python

pythonized answered on August 31, 2021 Popularity 10/10 Helpfulness 10/10

answer visualize correlation matrix python

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visualize correlation matrix python

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import seaborn as sns
df = sns.load_dataset('iris')
corr_matrix = df.corr()
corr_matrix.style.background_gradient(cmap='coolwarm')
# 'RdBu_r', 'BrBG_r', & PuOr_r are other good diverging colormaps

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Source: stackoverflow.com

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Contributed on Aug 31 2021

pythonized

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# Co-efficient and p-value
from scipy import stats
pearson_coef, p_val = stats.pearsonr(df["col1"], df["col2"])
# Visualize correlation
import seaborn as sns
sns.lmplot(x="col1", y="col2", data=df, ci=None)
plt.show()

# Find correlation among all columns in a dataframe
correlations = df.corr() 
# Use heatmap for correlation visualization (Scatterplot is not a good choice for dataframes with more than 2 variables)
sns.heatmap(correlations, annot=True) # use cmap='coolwarm' to provide color map
# Bend x label ticks 45 degree to avoid overlappings with each-other
plt.xticks(rotation=45) 
plt.title('Correlations')
plt.show()

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Source: Grepper

Tags: correlation corr

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Contributed on Jan 17 2023

Innocent Iguana

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visualize correlation matrix python

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