Delete durham_trees_analysis.py

durham_trees_analysis.py

@@ -1,72 +0,0 @@
-# -*- coding: utf-8 -*-
-"""durham_trees_analysis
-
-Automatically generated by Colaboratory.
-
-Original file is located at
-    https://colab.research.google.com/drive/1OjlRC7F_UICGJM59jzSoy1o2crZxqXCl
-"""
-
-# Save this code as a file named 'durham_trees_analysis.py'
-
-# Install required packages
-import subprocess
-
-# Install datasets package
-subprocess.run(["pip", "install", "datasets", "geopandas", "seaborn", "matplotlib", "mplcursors", "pandas"])
-
-# Import libraries
-from datasets import load_dataset
-import seaborn as sns
-import matplotlib.pyplot as plt
-import mplcursors
-import pandas as pd
-import geopandas as gpd
-
-# Load dataset
-dataset = load_dataset("Ziyuan111/DurhamTrees")
-
-# Convert dataset to pandas DataFrame
-df = pd.DataFrame(dataset['train'])
-
-# Interactive scatter plot with seaborn and mplcursors
-def plot_interactive_scatter():
-    scatter = sns.scatterplot(data=df, x='X', y='Y', hue='species')
-    plt.xlabel('X')
-    plt.ylabel('Y')
-    plt.legend([],[], frameon=False)
-    cursor = mplcursors.cursor(hover=True)
-
-    @cursor.connect("add")
-    def on_add(sel):
-        sel.annotation.set_text(df.iloc[sel.target.index]['species'])
-    plt.show()
-    plt.savefig('interactive_scatter.png')
-    display(Image('interactive_scatter.png'))
-
-# Plot tree planting sites with geopandas
-def plot_tree_sites():
-    gdf = gpd.GeoDataFrame(df, geometry=gpd.points_from_xy(df.X, df.Y))
-    durham_center = {'x': -78.898619, 'y': 35.994033}  # Durham, NC coordinates
-    fig, ax = plt.subplots(figsize=(10, 10))
-    gdf.plot(ax=ax, color='green')
-    buffer = 0.05
-    ax.set_xlim([durham_center['x'] - buffer, durham_center['x'] + buffer])
-    ax.set_ylim([durham_center['y'] - buffer, durham_center['y'] + buffer])
-    ax.set_title('Tree Planting Sites in Durham')
-    ax.set_xlabel('Longitude')
-    ax.set_ylabel('Latitude')
-    ax.set_axis_off()
-    plt.show()
-    plt.savefig('tree_sites.png')
-    display(Image('tree_sites.png'))
-
-# Print correlation matrix
-def print_correlation_matrix():
-    correlation_matrix = df[['diameterin', 'carbonstorage_lb']].corr()
-    print(correlation_matrix)
-
-# Call the functions
-plot_interactive_scatter()
-plot_tree_sites()
-print_correlation_matrix()