Update app.py

app.py

@@ -2,6 +2,72 @@ import pandas as pd
 import numpy as np
 import streamlit as st
 
+# import glob
+# import yaml
+from pathlib import Path
+from collections import defaultdict
+
+#########################################
+# Helpers Functions
+
+def filter_by_1col(df, col_name, query, exact_flag=False):
+
+    def check_valid_value(query, string, exact_flag=False):
+        if exact_flag:
+            if query.lower() == string.lower():
+                return True
+
+        elif query.lower() in string.lower():
+            return True
+        
+        return False
+
+    ok_flag_list = []
+    assert col_name in df.columns, "col_name must be valid"
+
+    for i, s in enumerate(df[col_name]):
+
+        if isinstance(s, list):
+            for s2 in s:
+                flag = check_valid_value(query, s2, exact_flag=exact_flag)
+                if flag: break
+        else:
+            flag = check_valid_value(query, s, exact_flag=exact_flag)
+
+        
+        ok_flag_list.append(flag)
+    
+    assert len(ok_flag_list) == len(df)
+    return np.array(ok_flag_list)
+
+def display_image(url, scale=0.5):
+    from urllib.request import urlopen
+    from PIL import Image
+
+    image = Image.open(urlopen(url))
+    st.image(image.resize(( int(image.width * scale), int(image.height * scale))))
+
+def display_heroes_from_df(df):
+    display_cols = ['name', 'color', 'star', 'class', 'speed', 'power', 'attack', 'defense', 'health', 'types', 'source', 'family']
+    st.dataframe(df[display_cols])
+
+    for i in range(len(df)):
+        url = df['image'].values[i]
+        display_image(url)
+        st.write(df['skill'].values[i])
+        for sp in df['effects'].values[i]:
+            st.write(sp)
+
+#########################################
+
+
 df = pd.read_csv('heroes_ep.csv')
-st.write('hello world')
-st.dataframe(df.head())
+
+idx_all = []
+idx_all.append(filter_by_1col(df, 'types', 'hit 3'))
+idx_all.append(filter_by_1col(df, 'effects', 'dispel'))
+idx_all.append(filter_by_1col(df, 'speed', 'fast', exact_flag=False))
+
+df2 = df[np.all(idx_all,axis=0)]
+
+display_heroes_from_df(df2.sort_values("power", ascending=False))