How to calculate corr from a dataframe with non-numeric columns

I have these data set as shown below:

which belong to Pokemon dataset
https://elitedatascience.com/wp-content/uploads/2022/07/Pokemon.csv

I want to plot the heatmap as shown below:

# Calculate correlations
corr = stats_df.corr()
 
# Heatmap
plt.figure(figsize=(9,8))
sns.heatmap(corr)

But I get this error below; how can I solve it?

>Solution :

To compute the (Pearson) correlation you need to have numeric data.

Try:

df = pd.read_csv('Pokemon.csv', encoding='latin1', index_col='#')
corr = df.select_dtypes('number').drop(columns=['Total', 'Generation']).corr()
sns.heatmap(data=corr)
plt.tight_layout()
plt.show()

Output:

>>> corr
               HP    Attack   Defense   Sp. Atk   Sp. Def     Speed
HP       1.000000  0.422386  0.239622  0.362380  0.378718  0.175952
Attack   0.422386  1.000000  0.438687  0.396362  0.263990  0.381240
Defense  0.239622  0.438687  1.000000  0.223549  0.510747  0.015227
Sp. Atk  0.362380  0.396362  0.223549  1.000000  0.506121  0.473018
Sp. Def  0.378718  0.263990  0.510747  0.506121  1.000000  0.259133
Speed    0.175952  0.381240  0.015227  0.473018  0.259133  1.000000