Analyzing National Parks Service

Overview

In this report I analyst National Parks Service about endangered species in different parks and their status.

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Libraries Used :

• pandas
• numpy
• seaborn
• matplotlib.pyplot
• re

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Methods Employed :

1. Data manipulation:

• merge()
• For loop
• Group by
• lambda
• loc
• isna()
• value_counts()
• dropna()
• min()
• mean()
• sum()
• max()
• size()
• duplicated()
• list
• compile
• reset_index

2. Data visualization:

• crosstab
• unstack
• autopct
• marker
• edgecolor
• bins
• linestyle
• label
• alpha
• plt.grid
• plt.axvline
• plt.ylim
• ascending
• pivot

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Graphs :

• Bar chart
• plt.hist (histogram plot)
• pie chart
• crosstab

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Key Findings :

• Protected species
• Most protected species among their own and all of the species
• Endangered species
• Threatened species
• Species of concern
• Specie and park in every conservation status

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Getting Started

1. Clone this repository.
2. Install the required libraries: pip install pandas numpy seaborn matplotlib re
3. Run the main Python script: biodiversity.ipynb

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Usage

• Explore the generated visualizations to gain insights into the data.
• Modify the code to experiment with different visualizations and analyses.

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Contributing

Feel free to submit issues or pull requests for improvements or additions.

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Author

Reza Sadeghi