Update app.py

app.py

@@ -1,68 +1,68 @@
-import pandas as pd 
-import plotly.express as px
-import streamlit as st
-
-st.set_page_config(
-    page_title='Data Analytics Portal',
-    page_icon='📊'
-)
-
-st.title(':blue[📊 Data Analytics Portal]')
-st.subheader(':grey[ An easy way to Analyse Data!!]', divider='green')
-
-file = st.file_uploader('Drop csv or excel file', type=['csv', 'xlsx'])
-if file:
-    if file.name.endswith('csv'):
-        data = pd.read_csv(file)
-    else:
-        data = pd.read_excel(file)
-    st.dataframe(data)
-    st.info('File is successfully Uploaded', icon='🚨')
-
-    st.subheader(':blue[Basic information of the dataset]', divider='green')
-    
-    tab1, tab2, tab3, tab4 = st.tabs(['Summary', 'Top and Bottom Rows', 'Data Types', 'Columns'])
-
-    with tab1:
-        st.write(f'There are {data.shape[0]} rows in dataset and {data.shape[1]} columns in the dataset')
-        st.subheader(':gray[Statistical summary of the dataset]')
-        st.dataframe(data.describe())
-    
-    with tab2:
-        st.subheader(':gray[Top Rows]')
-        toprows = st.slider('Number of rows you want', 1, data.shape[0], key='topslider')
-        st.dataframe(data.head(toprows))
-        st.subheader(':gray[Bottom Rows]')
-        bottomrows = st.slider('Number of rows you want', 1, data.shape[0], key='bottomslider')
-        st.dataframe(data.tail(bottomrows))
-    
-    with tab3:
-        st.subheader(':grey[Data types of column]')
-        st.dataframe(data.dtypes)
-    
-    with tab4:
-        st.subheader('Column Names in Dataset')
-        st.write(list(data.columns))
-
-    st.subheader(':blue[Column Values To Count]', divider='green')
-    
-    with st.expander('Value Count'):
-        col1, col2 = st.columns(2)
-        with col1:
-            column = st.selectbox('Choose Column name', options=list(data.columns))
-        with col2:
-            toprows = st.number_input('Top rows', min_value=1, step=1)
-        
-        count = st.button('Count')
-        if count:
-            result = data[column].value_counts().reset_index().head(toprows)
-            st.dataframe(result)
-            st.subheader('Visualization', divider='gray')
-            fig = px.bar(data_frame=result, x=column, y='count', text='count', template='plotly_white')
-            st.plotly_chart(fig)
-            fig = px.line(data_frame=result, x=column, y='count', text='count', template='plotly_white')
-            st.plotly_chart(fig)
-            fig = px.pie(data_frame=result, names=column, values='count')
-            st.plotly_chart(fig)
-else:
+import pandas as pd 
+import plotly.express as px
+import streamlit as st
+
+st.set_page_config(
+    page_title='Data Analytics Portal',
+    page_icon='📊'
+)
+
+st.title(':blue[📊 Data Analytics Portal]')
+st.subheader(':grey[ An easy way to Analyse Data!!]', divider='green')
+
+file = st.file_uploader('Drop CSV or Excel file', type=['csv', 'xlsx'])
+if file:
+    if file.name.endswith('csv'):
+        data = pd.read_csv(file)
+    else:
+        data = pd.read_excel(file)
+    st.dataframe(data)
+    st.info('File is successfully Uploaded', icon='🚨')
+
+    st.subheader(':blue[Basic information of the dataset]', divider='green')
+    
+    tab1, tab2, tab3, tab4 = st.tabs(['Summary', 'Top and Bottom Rows', 'Data Types', 'Columns'])
+
+    with tab1:
+        st.write(f'There are {data.shape[0]} rows in dataset and {data.shape[1]} columns in the dataset')
+        st.subheader(':gray[Statistical summary of the dataset]')
+        st.dataframe(data.describe())
+    
+    with tab2:
+        st.subheader(':gray[Top Rows]')
+        toprows = st.slider('Number of rows you want', 1, data.shape[0], key='topslider')
+        st.dataframe(data.head(toprows))
+        st.subheader(':gray[Bottom Rows]')
+        bottomrows = st.slider('Number of rows you want', 1, data.shape[0], key='bottomslider')
+        st.dataframe(data.tail(bottomrows))
+    
+    with tab3:
+        st.subheader(':grey[Data types of column]')
+        st.dataframe(data.dtypes)
+    
+    with tab4:
+        st.subheader('Column Names in Dataset')
+        st.write(list(data.columns))
+
+    st.subheader(':blue[Column Values To Count]', divider='green')
+    
+    with st.expander('Value Count'):
+        col1, col2 = st.columns(2)
+        with col1:
+            column = st.selectbox('Choose Column name', options=list(data.columns))
+        with col2:
+            toprows = st.number_input('Top rows', min_value=1, step=1)
+        
+        count = st.button('Count')
+        if count:
+            result = data[column].value_counts().reset_index().head(toprows)
+            st.dataframe(result)
+            st.subheader('Visualization', divider='gray')
+            fig = px.bar(data_frame=result, x=column, y='count', text='count', template='plotly_white')
+            st.plotly_chart(fig)
+            fig = px.line(data_frame=result, x=column, y='count', text='count', template='plotly_white')
+            st.plotly_chart(fig)
+            fig = px.pie(data_frame=result, names=column, values='count')
+            st.plotly_chart(fig)
+else:
     st.warning('Please upload a CSV or Excel file to get started', icon='⚠️')