Update app.py

app.py

@@ -8,7 +8,7 @@ from scipy.stats import chi2_contingency
 import numpy as np
 import seaborn as sns
 import matplotlib.pyplot as plt
-rows= []
+
 def cramers_V(var1,var2) :
   crosstab =np.array(pd.crosstab(var1,var2, rownames=None, colnames=None)) # Cross table building
   stat = chi2_contingency(crosstab)[0] # Keeping of the test statistic of the Chi2 test
@@ -18,7 +18,8 @@ def cramers_V(var1,var2) :
 
 def predict(file_obj):
     df = pd.read_csv(file_obj.name,dtype=str)
-    cat_df = df.select_dtypes(include=['object']).copy()
+    cat_df = df.select_dtypes(include=['object'])
+    rows= []
     for var1 in cat_df:
       col = []
       for var2 in cat_df :