| import streamlit as st | |
| import pandas as pd | |
| import plotly.express as px | |
| class GeospatialAnalyzer: | |
| def analyze_geospatial_data(self, df): | |
| lat_columns = [col for col in df.columns if 'lat' in col.lower()] | |
| lon_columns = [col for col in df.columns if 'lon' in col.lower()] | |
| if len(lat_columns) > 0 and len(lon_columns) > 0: | |
| lat_column = st.selectbox("Select latitude column", lat_columns) | |
| lon_column = st.selectbox("Select longitude column", lon_columns) | |
| map_type = st.selectbox("Select map type", ["Scatter Mapbox", "Density Mapbox"]) | |
| if map_type == "Scatter Mapbox": | |
| self.create_scatter_mapbox(df, lat_column, lon_column) | |
| elif map_type == "Density Mapbox": | |
| self.create_density_mapbox(df, lat_column, lon_column) | |
| else: | |
| st.write("No latitude and longitude columns found in the dataset.") | |
| def create_scatter_mapbox(self, df, lat_column, lon_column): | |
| st.subheader("Scatter Mapbox") | |
| color_column = st.selectbox("Select color column (optional)", ["None"] + df.columns.tolist()) | |
| size_column = st.selectbox("Select size column (optional)", ["None"] + df.columns.tolist()) | |
| fig = px.scatter_mapbox(df, | |
| lat=lat_column, | |
| lon=lon_column, | |
| color=None if color_column == "None" else color_column, | |
| size=None if size_column == "None" else size_column, | |
| zoom=3) | |
| fig.update_layout(mapbox_style="open-street-map") | |
| st.plotly_chart(fig) | |
| def create_density_mapbox(self, df, lat_column, lon_column): | |
| st.subheader("Density Mapbox") | |
| fig = px.density_mapbox(df, | |
| lat=lat_column, | |
| lon=lon_column, | |
| zoom=3, | |
| radius=10) | |
| fig.update_layout(mapbox_style="open-street-map") | |
| st.plotly_chart(fig) |