Update app.py

app.py

@@ -17,12 +17,15 @@ login(token = os.environ['hf_token'])
 dataset = load_dataset("irfantea/collections", data_files='Kombinasi.csv', split='train')
 df = dataset.to_pandas()
 
-@st.cache_data
+#@st.cache_data
 def load_data():
+    df = pd.read_csv("Kombinasi.csv")
     df["First name"] = df["First name"].astype("string")
     df["Grade/100.00 (Simulasi)"] = df["Grade/100.00 (Simulasi)"].astype(float)
     df["Grade/100.00 (Ujian 1)"] = df["Grade/100.00 (Ujian 1)"].astype(float)
-    df["Persentase Ujian 1 (15%)"] = (df["Grade/100.00 (Ujian 1)"].astype(float) * 0.15).round(2)
+    df["Grade/100.00 (Ujian 2)"] = df["Grade/100.00 (Ujian 2)"].astype(float)
+    df["Ujian 1 (15%)"] = (df["Grade/100.00 (Ujian 1)"].astype(float) * 0.15).round(2)
+    df["Ujian 2 (30%)"] = (df["Grade/100.00 (Ujian 2)"].astype(float) * 0.30).round(2)
     return df
 
 df = load_data()
@@ -30,9 +33,8 @@ df = load_data()
 def cari_npm(npm):
     df_cari = df[df["First name"] == npm]
     return df_cari
-
 def susun_data(data_npm):
-    columns_to_display = ["Surname", "First name",  "Grade/100.00 (Ujian 1)", "Persentase Ujian 1 (15%)"]
+    columns_to_display = ["Surname", "First name",  "Grade/100.00 (Ujian 1)", "Ujian 1 (15%)", "Grade/100.00 (Ujian 2)", "Ujian 2 (30%)"]
     st.table(data_npm[columns_to_display])
 
 colors = ['red', 'green', 'blue']
@@ -57,9 +59,36 @@ with kolom1:
     plt.xlabel('Rentang')
     plt.ylabel('Jumlah Mahasiswa')
     st.pyplot(plt)
+    average = df["Grade/100.00 (Ujian 1)"].mean()
+    median = df["Grade/100.00 (Ujian 1)"].median()
+    stdev = df["Grade/100.00 (Ujian 1)"].std()
+    st.info("Mean: " + str(average))
+    st.info("Median: " + str(median))
+    st.info("STDev: " + str(stdev))
+
+with kolom2:    
+    grades = df["Grade/100.00 (Ujian 2)"]
+    count_below_50 = (grades < 50).sum()
+    count_50_to_68 = ((grades >= 50) & (grades <= 68)).sum()
+    count_above_68 = (grades > 68).sum()
 
-with kolom2:
-    st.write("Ujian 2")
+    data = {
+        'Category': ['Below 50', '50 - 68', 'Above 68'],
+        'Count': [count_below_50, count_50_to_68, count_above_68]
+    }
+    df_counts = pd.DataFrame(data)
+    st.write("Ujian 2")    
+    plt.clf()  # Clear the current figure
+    plt.bar(df_counts['Category'], df_counts['Count'], color=colors)
+    plt.xlabel('Rentang')
+    plt.ylabel('Jumlah Mahasiswa')
+    st.pyplot(plt)
+    average = df["Grade/100.00 (Ujian 2)"].mean()
+    median = df["Grade/100.00 (Ujian 2)"].median()
+    stdev = df["Grade/100.00 (Ujian 2)"].std()
+    st.info("Mean: " + str(average))
+    st.info("Median: " + str(median))
+    st.info("STDev: " + str(stdev))
 
 with kolom3:
     st.write("Ujian Final")