From 3907e05d34aed2f422d999b30760bc26b76faee4 Mon Sep 17 00:00:00 2001 From: Sunita1212 Date: Thu, 15 May 2025 08:32:19 +0000 Subject: [PATCH] Main --- src/1-line-plot.ipynb | 58 ++++++++++++++++++++++++++++++++- src/2-bar-plot.ipynb | 66 +++++++++++++++++++++++++++++++++++-- src/3-scatter-plot.ipynb | 57 +++++++++++++++++++++++++++++++- src/4-pie-chart.ipynb | 53 +++++++++++++++++++++++++++++- src/5-subplot.ipynb | 68 ++++++++++++++++++++++++++++++++++++++- src/6-histogram.ipynb | 52 +++++++++++++++++++++++++++++- src/output.png | Bin 0 -> 13444 bytes 7 files changed, 347 insertions(+), 7 deletions(-) create mode 100644 src/output.png diff --git a/src/1-line-plot.ipynb b/src/1-line-plot.ipynb index eab74494..52c6ac05 100644 --- a/src/1-line-plot.ipynb +++ b/src/1-line-plot.ipynb @@ -16,11 +16,67 @@ "# TASK: Create a line plot with x values ranging from 0 to 10 and y values as the square of x.\n", "# Customize the plot by adding a title, labels for both axes, and a grid." ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "\n", + "# Create x values from 0 to 10\n", + "x = np.linspace(0, 10, 100)\n", + "# Compute y values as the square of x\n", + "y = x ** 2\n", + "\n", + "# Create the plot\n", + "plt.figure(figsize=(8, 5))\n", + "plt.plot(x, y, label='y = x^2', color='blue')\n", + "\n", + "# Add title and labels\n", + "plt.title('Line Plot of y = x^2')\n", + "plt.xlabel('x')\n", + "plt.ylabel('y')\n", + "\n", + "# Add grid\n", + "plt.grid(True)\n", + "\n", + "# Show the plot\n", + "plt.legend()\n", + "plt.show()\n" + ] } ], "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, "language_info": { - "name": "python" + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" } }, "nbformat": 4, diff --git a/src/2-bar-plot.ipynb b/src/2-bar-plot.ipynb index 9d3fb712..03752f31 100644 --- a/src/2-bar-plot.ipynb +++ b/src/2-bar-plot.ipynb @@ -9,18 +9,80 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# TASK: Create a bar plot with the following data: categories = ['A', 'B', 'C', 'D'] and values = [5, 7, 3, 9].\n", "# Use different colors for each bar and add a title to the plot." ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "# Data\n", + "categories = ['A', 'B', 'C', 'D']\n", + "values = [5, 7, 3, 9]\n", + "colors = ['red', 'green', 'blue', 'orange'] # Different colors for each bar\n", + "\n", + "# Create the plot\n", + "plt.figure(figsize=(8, 5))\n", + "plt.bar(categories, values, color=colors)\n", + "\n", + "# Add title and labels\n", + "plt.title('Bar Plot of Categories and Values')\n", + "plt.xlabel('Categories')\n", + "plt.ylabel('Values')\n", + "\n", + "# Show the plot\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [ + "categories colors values" + ] + }, + "outputs": [], + "source": [] } ], "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, "language_info": { - "name": "python" + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" } }, "nbformat": 4, diff --git a/src/3-scatter-plot.ipynb b/src/3-scatter-plot.ipynb index 9bed601f..bb756586 100644 --- a/src/3-scatter-plot.ipynb +++ b/src/3-scatter-plot.ipynb @@ -16,11 +16,66 @@ "# TASK: Create a scatter plot with x = [1, 2, 3, 4, 5] and y = [2, 4, 6, 8, 10].\n", "# Annotate each point with its (x, y) value, and set the title as 'Scatter Plot with Annotations'." ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "# Data\n", + "x = [1, 2, 3, 4, 5]\n", + "y = [2, 4, 6, 8, 10]\n", + "\n", + "# Create the plot\n", + "plt.figure(figsize=(8, 5))\n", + "plt.scatter(x, y, color='blue')\n", + "\n", + "# Annotate each point with its (x, y) value\n", + "for i in range(len(x)):\n", + " plt.annotate(f'({x[i]}, {y[i]})', (x[i], y[i]), textcoords=\"offset points\", xytext=(5,5), ha='center')\n", + "\n", + "# Add title and labels\n", + "plt.title('Scatter Plot with Annotations')\n", + "plt.xlabel('x')\n", + "plt.ylabel('y')\n", + "\n", + "# Show the plot\n", + "plt.grid(True)\n", + "plt.show()\n" + ] } ], "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, "language_info": { - "name": "python" + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" } }, "nbformat": 4, diff --git a/src/4-pie-chart.ipynb b/src/4-pie-chart.ipynb index eedc5b94..802dd999 100644 --- a/src/4-pie-chart.ipynb +++ b/src/4-pie-chart.ipynb @@ -16,11 +16,62 @@ "# TASK: Create a pie chart with the following data: labels = ['Python', 'Java', 'C++', 'JavaScript'] and sizes = [40, 25, 20, 15].\n", "# Display the percentages on the chart using autopct." ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "# Data\n", + "labels = ['Python', 'Java', 'C++', 'JavaScript']\n", + "sizes = [40, 25, 20, 15]\n", + "\n", + "# Create the pie chart\n", + "plt.figure(figsize=(8, 6))\n", + "plt.pie(sizes, labels=labels, autopct='%1.1f%%', startangle=140)\n", + "\n", + "# Add title\n", + "plt.title('Programming Language Popularity')\n", + "\n", + "# Make sure pie chart is a circle\n", + "plt.axis('equal')\n", + "\n", + "# Show the plot\n", + "plt.show()\n" + ] } ], "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, "language_info": { - "name": "python" + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" } }, "nbformat": 4, diff --git a/src/5-subplot.ipynb b/src/5-subplot.ipynb index 98e4fa95..1f2d26f2 100644 --- a/src/5-subplot.ipynb +++ b/src/5-subplot.ipynb @@ -16,11 +16,77 @@ "# TASK: Create a 2x2 subplot layout.\n", "# Plot a line chart in the first subplot, a bar chart in the second, a scatter plot in the third, and a pie chart in the fourth." ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "# Sample data for each plot\n", + "x = [1, 2, 3, 4, 5]\n", + "y_line = [i**2 for i in x]\n", + "y_bar = [5, 7, 3, 9, 6]\n", + "y_scatter = [2, 4, 6, 8, 10]\n", + "labels_pie = ['Python', 'Java', 'C++', 'JavaScript']\n", + "sizes_pie = [40, 25, 20, 15]\n", + "\n", + "# Create 2x2 subplot layout\n", + "fig, axs = plt.subplots(2, 2, figsize=(12, 10))\n", + "\n", + "# Line chart\n", + "axs[0, 0].plot(x, y_line, color='blue')\n", + "axs[0, 0].set_title('Line Chart')\n", + "\n", + "# Bar chart\n", + "axs[0, 1].bar(x, y_bar, color='green')\n", + "axs[0, 1].set_title('Bar Chart')\n", + "\n", + "# Scatter plot\n", + "axs[1, 0].scatter(x, y_scatter, color='red')\n", + "axs[1, 0].set_title('Scatter Plot')\n", + "\n", + "# Pie chart\n", + "axs[1, 1].pie(sizes_pie, labels=labels_pie, autopct='%1.1f%%', startangle=140)\n", + "axs[1, 1].set_title('Pie Chart')\n", + "axs[1, 1].axis('equal') # Equal aspect ratio for pie chart\n", + "\n", + "# Adjust layout\n", + "plt.tight_layout()\n", + "plt.show()\n" + ] } ], "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, "language_info": { - "name": "python" + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" } }, "nbformat": 4, diff --git a/src/6-histogram.ipynb b/src/6-histogram.ipynb index 5e6e6b60..c61786e8 100644 --- a/src/6-histogram.ipynb +++ b/src/6-histogram.ipynb @@ -16,11 +16,61 @@ "# TASK: Create a histogram for the following data: data = [1, 2, 2, 3, 3, 3, 4, 4, 4, 4, 5].\n", "# Customize the histogram with a title, labels for the x-axis, and a specific color for the bars." ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "# Data\n", + "data = [1, 2, 2, 3, 3, 3, 4, 4, 4, 4, 5]\n", + "\n", + "# Create the histogram\n", + "plt.figure(figsize=(8, 5))\n", + "plt.hist(data, bins=5, color='skyblue', edgecolor='black')\n", + "\n", + "# Customize the plot\n", + "plt.title('Histogram of Data Values')\n", + "plt.xlabel('Value')\n", + "plt.ylabel('Frequency')\n", + "\n", + "# Show the plot\n", + "plt.grid(True)\n", + "plt.show()\n" + ] } ], "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, "language_info": { - "name": "python" + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" } }, "nbformat": 4, diff --git a/src/output.png b/src/output.png new 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