The Point that you're missing

Tips for your data analysis and AI code





# 1. Easy on your eyes, easy to your analysis

sns.countplot(data=df , x ='target_column', hue='satisfaction')

df['target_column'].value_counts().plot(kind='bar') 



# 2. Save time

df['Bool'].loc[df['Bool'] == 1] = 'Y'
df['Bool'].loc[df['Bool'] == 0] = 'N'



# 3. Don't forget to invers transforming

le = LabelEncoder()
df['column'] = le.fit_transform(df['column'])
le.inverse_transform(result)
    
    
    
# 4. Why not pretty?

corr_data = df.corr()
fig, ax = plt.subplots(figsize=(12,10))

mask = np.zeros_like(corr_data)
mask[np.triu_indices_from(mask)] = True

sns.heatmap(corr_data, 
            annot = True,  
            mask=mask,     
            linewidths=1.,  
            cbar_kws={"shrink": .5}, 
            vmin = -1,
            vmax = 1   
           )  
plt.show()

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