diff --git a/.devcontainer/.Dockerfile b/.devcontainer/.Dockerfile index e69de29..1c3275e 100644 --- a/.devcontainer/.Dockerfile +++ b/.devcontainer/.Dockerfile @@ -0,0 +1,6 @@ +FROM python:3.12.5 + +WORKDIR /app + +COPY requirements.txt . +RUN pip install --no-cache-dir -r requirements.txt \ No newline at end of file diff --git a/.devcontainer/devcontainer.json b/.devcontainer/devcontainer.json index e69de29..f35055b 100644 --- a/.devcontainer/devcontainer.json +++ b/.devcontainer/devcontainer.json @@ -0,0 +1,25 @@ +{ + "name": "My Dev Container", + "dockerFile": "Dockerfile", + // "features": { + // "ghcr.io/devcontainers/features/docker-in-docker:2": {} + // }, + "customizations": { + "vscode": { + // "settings": { + // "python.pythonPath": "/usr/local/bin/python", + // "editor.formatOnSave": true + // }, + "extensions": [ + "ms-python.python", + "ms-python.vscode-pylance", + "ms-python.autopep8" + ] + } + }, + //"postCreateCommand": "pip install -r requirements.txt", // Runs after the container is created, to install dependencies + "forwardPorts": [ + 4040 + ], // List of ports to forward from the container + "remoteUser": "vscode" // Default user to run commands as +} \ No newline at end of file diff --git a/.github/workflows/main.yaml b/.github/workflows/main.yaml index e69de29..3d3ad48 100644 --- a/.github/workflows/main.yaml +++ b/.github/workflows/main.yaml @@ -0,0 +1,34 @@ +name: RamilIndividualProject1_GithubActions + +on: + push: + branches: + - main + pull_request: + branches: + - main + +jobs: + build-and-test: + runs-on: ubuntu-latest + + steps: + - name: Checkout code + uses: actions/checkout@v3 + + - name: Set up Python + uses: actions/setup-python@v4 + with: + python-version: '3.12.5' + + - name: Create environment + run: make install + + - name: Format the code + run: make format + + - name: Run Lint + run: make lint + + - name: Run tests + run: make test_code \ No newline at end of file diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..34ab06b --- /dev/null +++ b/.gitignore @@ -0,0 +1 @@ +**cache** \ No newline at end of file diff --git a/Makefile b/Makefile index 65f19a3..73acc73 100644 --- a/Makefile +++ b/Makefile @@ -1,18 +1,17 @@ install: - pip install --upgrade pip && pip install -r requirements.txt + pip3 install -r requirements.txt format: - black *.py - + black src/*.py + black test/*.py +test_code: + pytest -vv --nbval -cov=my_lib -cov=main test/test_*.py *.ipynb lint: - ruff check *.py - + ruff check src/*.py + ruff check test/*.py container-lint: docker run --rm -i hadolint/hadolint < .devcontainer/Dockerfile -test: - python -m pytest -vv --nbval -cov=my_lib -cov=main test_*.py *.ipynb - all: install format lint container-lint test generate_and_push: diff --git a/data/correlation_matrix.png b/data/correlation_matrix.png new file mode 100644 index 0000000..3f5cf83 Binary files /dev/null and b/data/correlation_matrix.png differ diff --git a/data/histogram.png b/data/histogram.png new file mode 100644 index 0000000..34bff53 Binary files /dev/null and b/data/histogram.png differ diff --git a/data/line_graph.png b/data/line_graph.png new file mode 100644 index 0000000..4201617 Binary files /dev/null and b/data/line_graph.png differ diff --git a/main.ipynb b/main.ipynb new file mode 100644 index 0000000..1cdc71b --- /dev/null +++ b/main.ipynb @@ -0,0 +1,304 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "from src.lib import (\n", + " get_data,\n", + " get_max_val,\n", + " get_min_val,\n", + " get_summary,\n", + " get_std_val,\n", + " get_histogram,\n", + " get_line_graph,\n", + " get_correlation_matrix,\n", + ")\n", + "\n", + "\n", + "remote_path = \"https://raw.githubusercontent.com/Ramil-cyber/Ramil-Individual-Project-1/refs/heads/main/data/shanghai_ranking_2024.csv\"\n", + "\n", + "\n", + "data = get_data(remote_path)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "# NBVAL_IGNORE_OUTPUT\n", + "\n", + "\n", + "assert get_max_val(data, col=\"N&S\") == 100.0\n", + "assert get_min_val(data, col=\"PUB\") == 9.3" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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AlumniAwardHiciN&SPUBPCP
count1000.0000001000.000001000.000000989.0000001000.0000001000.000000
mean4.5096003.7812010.73440010.57512635.11300019.655300
std10.10320111.4553810.94926510.63724713.6844958.800436
min0.0000000.000000.0000000.0000009.3000008.600000
25%0.0000000.000000.0000003.90000025.77500014.100000
50%0.0000000.000009.2000007.30000031.70000017.600000
75%0.0000000.0000014.60000013.30000041.42500023.000000
max100.000000100.00000100.000000100.000000100.000000100.000000
\n", + "
" + ], + "text/plain": [ + " Alumni Award Hici N&S PUB \\\n", + "count 1000.000000 1000.00000 1000.000000 989.000000 1000.000000 \n", + "mean 4.509600 3.78120 10.734400 10.575126 35.113000 \n", + "std 10.103201 11.45538 10.949265 10.637247 13.684495 \n", + "min 0.000000 0.00000 0.000000 0.000000 9.300000 \n", + "25% 0.000000 0.00000 0.000000 3.900000 25.775000 \n", + "50% 0.000000 0.00000 9.200000 7.300000 31.700000 \n", + "75% 0.000000 0.00000 14.600000 13.300000 41.425000 \n", + "max 100.000000 100.00000 100.000000 100.000000 100.000000 \n", + "\n", + " PCP \n", + "count 1000.000000 \n", + "mean 19.655300 \n", + "std 8.800436 \n", + "min 8.600000 \n", + "25% 14.100000 \n", + "50% 17.600000 \n", + "75% 23.000000 \n", + "max 100.000000 " + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# NBVAL_IGNORE_OUTPUT\n", + "\n", + "get_summary(data)" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# NBVAL_IGNORE_OUTPUT\n", + "\n", + "get_histogram(dataframe=data, col=\"PCP\", img_path=\"data/histogram.png\")" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# NBVAL_IGNORE_OUTPUT\n", + "\n", + "get_line_graph(\n", + " dataframe=data, x_col=\"Alumni\", y_col=\"PUB\", img_path=\"data/line_graph.png\"\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# NBVAL_IGNORE_OUTPUT\n", + "\n", + "get_correlation_matrix(df=data, img_path=\"data/correlation_matrix\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "myenv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.19" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/requirements.txt b/requirements.txt index e69de29..3a45ac9 100644 --- a/requirements.txt +++ b/requirements.txt @@ -0,0 +1,18 @@ +tabulate==0.9.0 +nbval==0.11.0 +black==24.8.0 +iniconfig==2.0.0 +ipykernel==6.29.5 +ipython==8.26.0 +matplotlib==3.9.2 +matplotlib-inline==0.1.7 +nbconvert==7.16.4 +nbformat==5.10.4 +nbval==0.11.0 +numpy==2.1.0 +pandas==2.2.2 +psutil==6.0.0 +pylint==3.2.7 +pytest==8.3.3 +ruff==0.6.6 +setuptools==73.0.1 diff --git a/main.py b/src/__init__.py similarity index 100% rename from main.py rename to src/__init__.py diff --git a/src/lib.py b/src/lib.py index e69de29..840edc5 100644 --- a/src/lib.py +++ b/src/lib.py @@ -0,0 +1,69 @@ +import pandas as pd +import matplotlib.pyplot as plt + + +def get_data(path): + """Read and return the dataframe""" + df = pd.read_csv(path) + return df + + +def get_max_val(df, col): + return df[col].max() + + +def get_min_val(df, col): + return df[col].min() + + +def get_std_val(df, col): + return df[col].std() + + +def get_summary(df): + return df.describe() + + +def get_histogram(dataframe, col, img_path, show_image=False): + """ + Return histogram from given column based on given dataframe + """ + plt.hist(dataframe[col], bins=5, edgecolor="black") + plt.title(f"Histogram of {col}") + plt.xlabel("Values") + plt.ylabel("Frequency") + plt.savefig(img_path, dpi=300) + if show_image: + plt.show() + return True + + +def get_line_graph(dataframe, x_col, y_col, img_path, show_image=False): + """ + Return line graph from given x and y columns based on given dataframe + """ + plt.close() + dataframe.plot(kind="line", x=x_col, y=y_col, legend=True) + + plt.title("Line Graph of Value over Time") + plt.xlabel(x_col) + plt.ylabel(y_col) + plt.savefig(img_path, dpi=300) + # Show plot + if show_image: + plt.show() + return True + + +def get_correlation_matrix(df, img_path, show_image=False): + df = df.select_dtypes(float) + plt.figure(figsize=(14, 10)) + plt.matshow( + df.corr(), + cmap="coolwarm", + ) + plt.title("Correlation Matrix", pad=20) + plt.colorbar() + plt.savefig(img_path) + if show_image: + plt.show() diff --git a/src/main.py b/src/main.py index e69de29..4ec44b3 100644 --- a/src/main.py +++ b/src/main.py @@ -0,0 +1,59 @@ +import pandas as pd +from lib import ( + get_summary, + get_histogram, + get_line_graph, + get_correlation_matrix, +) + + +remote_path = "https://raw.githubusercontent.com/Ramil-cyber/Ramil-Individual-Project-1/refs/heads/main/data/shanghai_ranking_2024.csv" + + +def calculate_iqr(df, column): + """ + Calculate the Interquartile Range (IQR) of a given column in the DataFrame. + Parameters: + df (pandas.DataFrame): The input DataFrame. + column (str): The name of the column for which to calculate the IQR. + Returns: + float: The calculated IQR of the column. + """ + # Get the first quartile (25th percentile) + Q1 = df[column].quantile(0.25) + # Get the third quartile (75th percentile) + Q3 = df[column].quantile(0.75) + # Calculate the IQR + IQR = Q3 - Q1 + return IQR + + +def save_to_md(data): + """save summary report to markdown""" + describe_df = get_summary(data) + markdown_table1 = describe_df.to_markdown() + # Write the markdown table to a file + with open("summary_statistics.md", "w", encoding="utf-8") as file: + file.write("Describe:\n") + file.write(markdown_table1) + file.write("\n\n") # Add a new line + file.write("![alt_text_histogram](data/histogram.png)\n") + file.write("\n\n") # Add a new line + file.write("![alt_text_line_graph](data/line_graph.png)\n") + file.write("\n\n") # Add a new line + file.write("![alt_text_correlation_matrix](data/correlation_matrix.png)\n") + + +if __name__ == "__main__": + df = pd.read_csv(remote_path) + + top_100_df = df.iloc[:100, :] + get_histogram(top_100_df, col="PCP", img_path="data/histogram.png") + get_line_graph( + top_100_df, x_col="Alumni", y_col="PUB", img_path="data/line_graph.png" + ) + get_correlation_matrix(top_100_df, img_path="data/correlation_matrix") + + save_to_md(df) + + print(calculate_iqr(top_100_df, column="Award")) # 26.650000000000006 diff --git a/test/__init__.py b/test/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/test/test_lib.py b/test/test_lib.py new file mode 100644 index 0000000..1aeba6e --- /dev/null +++ b/test/test_lib.py @@ -0,0 +1,49 @@ +from src.lib import ( + get_data, + get_max_val, + get_min_val, + get_std_val, + get_histogram, + get_line_graph, + get_correlation_matrix, +) + +import os +import pandas as pd + +remote_path = "https://raw.githubusercontent.com/Ramil-cyber/Ramil-Individual-Project-1/refs/heads/main/data/shanghai_ranking_2024.csv" + + +def test_df(): + df = get_data(remote_path) + + assert df.shape[0] == 1000 + assert df.shape[1] == 9 + assert isinstance(df, pd.DataFrame) + + +def test_funcs(): + df = get_data(remote_path) + + assert int(get_max_val(df, "N&S")) == 100 + assert int(get_std_val(df, "N&S")) == 10 + assert int(get_min_val(df, "PUB")) == 9 + + +def test_visualization(): + df = get_data(remote_path) + + get_histogram(df, "PCP", img_path="data/test_histogram.png") + assert os.path.exists("data/test_histogram.png") + os.remove("data/test_histogram.png") + + get_line_graph(df, x_col="Alumni", y_col="PUB", img_path="data/test_line_graph.png") + assert os.path.exists("data/test_line_graph.png") + os.remove("data/test_line_graph.png") + + get_correlation_matrix(df, img_path="data/test_correlation_matrix.png") + assert os.path.exists("data/test_correlation_matrix.png") + os.remove("data/test_correlation_matrix.png") + + +test_funcs() diff --git a/test/test_main.py b/test/test_main.py index e69de29..48ceb8e 100644 --- a/test/test_main.py +++ b/test/test_main.py @@ -0,0 +1 @@ +# from src.main import