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Data Analysis, Visualization - Coggle Diagram
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Visualization
Distribution
Histogram
sns.displot(df['column_name'], bins=number)
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Bar
sns.countplot(data=df, x=['column_name'], hue='hue_column')
Stacked Column chart
df.set_index('columnforx').plot(kind='bar', stacked=True, y=['columnfory1','columnfory2'], color=['blue', 'red'])
Pie Chart
Column Wise
df.set_index('columnforx').plot.pie(y='columnfory', autopct='%1.1f%%')
df.set_index('columnforx').plot.pie(subplots=True, autopct='%1.1f%%')
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Density Plot
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2 plots in 1 row : df[['column1','column2']].plot(kind='density', subplots=True, layout=(1,2), sharex=False, figsize=(15,5))
2 dimension : sns.jointplot(data=df, x='column1', y='column2', kind = 'kde')
Violin Plot
sns.violinplot(data=df, x='column')
Correlation
Heatmap
Identify the correlation coefficient between all numerical columns
----- sns.heatmap(df.corr(), annot=True, cmap='coolwarm', fmt=".2f")
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Scatter Plot
sns.relplot(x='column1', y='column2', hue=''categorical_column3, data=df)
plt.scatter(df['column1'], df['column2'])
Scatter plot + Histogram
---- sns.jointplot(data=df, x='column1', y='column2')
Scatter plot + Trend
sns.lmplot(x='column1', y='column2', hue=''column3, data=df)
Outlier Detection
Boxplot
sns.boxpot(data=df, x='column')