Create app.py

app.py

@@ -0,0 +1,52 @@
+import streamlit as st
+import pandas as pd
+
+st.set_page_config(layout="centered")
+
+@st.cache_data(show_spinner=False)
+def load_data(file_path):
+    dataset = pd.read_csv(file_path)
+    return dataset
+
+
+@st.cache_data(show_spinner=False)
+def split_frame(input_df, rows):
+    df = [input_df.loc[i : i + rows - 1, :] for i in range(0, len(input_df), rows)]
+    return df
+
+
+file_path = st.file_uploader("Select CSV file to upload", type=["csv"])
+if file_path:
+    dataset = load_data(file_path)
+    top_menu = st.columns(3)
+    with top_menu[0]:
+        sort = st.radio("Sort Data", options=["Yes", "No"], horizontal=1, index=1)
+    if sort == "Yes":
+        with top_menu[1]:
+            sort_field = st.selectbox("Sort By", options=dataset.columns)
+        with top_menu[2]:
+            sort_direction = st.radio(
+                "Direction", options=["⬆️", "⬇️"], horizontal=True
+            )
+        dataset = dataset.sort_values(
+            by=sort_field, ascending=sort_direction == "⬆️", ignore_index=True
+        )
+    pagination = st.container()
+
+    bottom_menu = st.columns((4, 1, 1))
+    with bottom_menu[2]:
+        batch_size = st.selectbox("Page Size", options=[25, 50, 100])
+    with bottom_menu[1]:
+        total_pages = (
+            int(len(dataset) / batch_size) if int(len(dataset) / batch_size) > 0 else 1
+        )
+        current_page = st.number_input(
+            "Page", min_value=1, max_value=total_pages, step=1
+        )
+    with bottom_menu[0]:
+        st.markdown(f"Page **{current_page}** of **{total_pages}** ")
+
+
+
+    pages = split_frame(dataset, batch_size)
+    pagination.dataframe(data=pages[current_page - 1], use_container_width=True)