How to find if any variable which is normally distributed in pandas dataframe
You can do like so:
from scipy.stats import normaltest

def normal_test(frame, significance = .01, plot = False):
    &quot;&quot;&quot;
    Function to perform ks test and test against normal distribution using  
    D’Agostino, R. B. (1971), “An omnibus test of normality for moderate and large sample size”
    
    frame: a pandas dataframe
    significance: float. Alpha level for which the null hypotesis will be rejected (H0: series comes from a normal distribution)
    plot: Boolean, whether or not plot a histogram for resulting columns
    
    returns a dataframe with only those columns that follow a normal distribution according to test.
&quot;&quot;&quot;

    columns = frame.columns.tolist()

    for col in columns:
        aux = frame[col]
    
        _, p = normaltest(aux)
    
    if p &lt;= significance:
        frame.drop(col, axis = 1, inplace = True)
        
    if plot:
        fig, ax = plt.subplots(1,1, figsize = (12,7))
    
    frame.hist(ax = ax, color = &quot;darkred&quot;, edgecolor = &quot;black&quot;);
        
    return frame

Test data:
 A = pd.DataFrame({&quot;normal&quot;:np.random.normal(size = 1000),
                  &quot;exponential&quot;:np.random.exponential(size = 1000),
                  &quot;poisson&quot;:np.random.poisson(size = 1000),
                  &quot;normal_2&quot;:np.random.normal(size = 1000)})





result = normal_test(A)