Create app.py

app.py

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+import pandas as pd
+import streamlit as st
+import seaborn as sns
+import matplotlib.pyplot as plt
+
+data = pd.read_csv('solar_power_data.csv')
+data['datetime'] = pd.to_datetime(data[['year', 'month', 'day', 'hour']])
+data = data.set_index('datetime')
+data = data.drop(columns=['year', 'month', 'day', 'hour'])
+
+months = range(1, 13)
+years = sorted(data.index.year.unique())
+
+st.title('Solar Power Generation Data')
+
+selected_year = st.sidebar.selectbox('Select Year', years)
+selected_month = st.sidebar.selectbox('Select Month', months)
+
+month_data = data[(data.index.year == selected_year) & (data.index.month == selected_month)]
+
+st.subheader(f'Solar Power Generation for {selected_year} - Month {selected_month:02d}')
+
+plt.figure(figsize=(14, 7))
+fig, ax = plt.subplots(figsize=(14, 7))
+fig.patch.set_facecolor('black')
+ax.set_facecolor('black')
+
+sns.lineplot(x=month_data.index, y=month_data['Watts_per_hr'], color='#00FF00', linewidth=2.5, ax=ax)
+
+ax.set_title(f'Solar Power Generation for {selected_year} - Month {selected_month:02d}', fontsize=18, weight='bold', color='white')
+ax.set_xlabel('Date', fontsize=14, color='white')
+ax.set_ylabel('Watts per Hour', fontsize=14, color='white')
+ax.tick_params(axis='both', colors='white')
+ax.grid(True, linestyle='--', alpha=0.7, color='gray')
+
+sns.despine()
+plt.xticks(rotation=45)
+plt.tight_layout()
+
+st.pyplot(fig)
+
+st.subheader('Data Table')
+st.write(month_data)