{"id":1941,"date":"2019-08-08T12:00:00","date_gmt":"2019-08-08T10:00:00","guid":{"rendered":"https:\/\/kindsonthegenius.com\/blog\/plotting-tutorial-in-python-with-matplolib-pyplot-part-2\/"},"modified":"2026-07-05T03:24:14","modified_gmt":"2026-07-05T01:24:14","slug":"plotting-tutorial-in-python-with-matplolib-pyplot-part-2","status":"publish","type":"post","link":"https:\/\/kindsonthegenius.com\/blog\/plotting-tutorial-in-python-with-matplolib-pyplot-part-2\/","title":{"rendered":"Plotting Tutorial in Python with Matplolib.pyplot \u2013 Part 2"},"content":{"rendered":"

This is Part 2 of Plotting Tutorial in Python with Matplotlib.pyplot. You can find Part 1 here.<\/a><\/p>\n

Here, we cover the following<\/p>\n

    \n
  1. Example 2 – Plotting the Heart Curve<\/a><\/li>\n
  2. Example 3 – The Figure 8 Curve<\/a><\/li>\n
  3. Working with Subplots<\/a><\/li>\n
  4. Working with Scatterplots<\/a><\/li>\n
  5. Working with Histograms<\/a><\/li>\n
  6. Creating a Bar Plot<\/a><\/li>\n<\/ol>\n

     <\/p>\n

    1. Example 2 – Plotting the Heart Curve<\/strong><\/h5>\n

    This is a curve with the shape of a heart! It is based on the formulas below:<\/p>\n

    \"\"<\/p>\n

    The Python code for the heart plot is given in the figure below:<\/p>\n

    # We plot the line with RGB tuple (red = 1, green = 0.2, blue = 0.5)<\/span>\n# and 20pt line width<\/span>\nplt.<\/span>plot(x, y, c=<\/span>'red'<\/span>, lw=<\/span>18<\/span>)\n\n# Add features to our figure<\/span>\nplt.<\/span>title('My Heart!'<\/span>)\nplt.<\/span>axis('equal'<\/span>)\nplt.<\/span>axis('off'<\/span>)\nplt.<\/span>show()\n<\/pre>\n
     <\/p>\n
    The output is shown below:<\/p>\n
    \"Heart<\/p>\n
    I recommend you try it. Also change up things a bit to see how it appears. For example, change the color, linewidth etc.<\/p>\n
     <\/p>\n
    2. Example 3 – The Figure 8 Curve<\/strong><\/h5>\n
    This is another interesting curve to create. Besides, it is quite easy to work with. It is based on the following trigonometric equations:<\/p>\n
    \"\"<\/p>\n
    The Python code is given below:<\/p>\n
    # 8. Example 3 - The Figure 8 Curve<\/span>\nt =<\/span> np.<\/span>linspace(0<\/span>, 2<\/span> *<\/span> np.<\/span>pi, 40<\/span>)\nx =<\/span> np.<\/span>sin(t)\ny =<\/span> np.<\/span>sin(t) *<\/span> np.<\/span>cos(t)\n\n# plt.subplot(2,1,1)<\/span>\nplt.<\/span>plot(x, y, \n         markersize =<\/span> 10<\/span>,\n         linewidth =<\/span> 15<\/span>,\n         color =<\/span> 'green'<\/span>,\n        )\n\nplt.<\/span>show()\n<\/pre>\n
     <\/p>\n
    The output of the code is given below:<\/p>\n
    \"\"<\/p>\n
     <\/p>\n
    3. Working with Subplots<\/strong><\/h5>\n
    Subplots allow you to display two or more plots in a grid form with each curve in its own rectangular plot. The\u00a0plt.subplot()<\/strong> function takes at least 3 inputs\u00a0n<\/em>,\u00a0m<\/em>\u00a0and\u00a0i<\/em>\u00a0and creates a figure with a\u00a0n<\/em>\u00a0<\/em>by\u00a0m<\/em> grid of subplots and then sets the\u00a0i<\/em>th<\/em> subplot (counting across the rows) as the current plot (ie. current axes object).<\/p>\n
    Once, you call the subplot function, then the next plot following it is plotted on the particular subplot specified.<\/p>\n
    Let’s take and example<\/p>\n
    We’ll plot four different curves in 4 subplots. The equations of the curves is given as:<\/p>\n
    \"\"<\/p>\n
    The Python code is given below;<\/p>\n
    t =<\/span> np.<\/span>linspace(0<\/span>,4<\/span>,200<\/span>)\nf1 =<\/span> 1<\/span>\/<\/span>2<\/span> +<\/span> np.<\/span>sin(2<\/span> *<\/span> np.<\/span>pi *<\/span> t) \/<\/span> np.<\/span>pi\nf2 =<\/span> f1  -<\/span> np.<\/span>sin(4<\/span> *<\/span> np.<\/span>pi *<\/span> t) \/<\/span> 2<\/span> *<\/span> np.<\/span>pi\nf3 =<\/span> f2  +<\/span> np.<\/span>sin(6<\/span> *<\/span> np.<\/span>pi *<\/span> t) \/<\/span> 3<\/span> *<\/span> np.<\/span>pi\nf4 =<\/span> f3  -<\/span> np.<\/span>sin(8<\/span> *<\/span> np.<\/span>pi *<\/span> t) \/<\/span> 4<\/span> *<\/span> np.<\/span>pi\n\nplt.<\/span>subplot(2<\/span>,2<\/span>,1<\/span>)\nplt.<\/span>plot(t, f1)\nplt.<\/span>title('N = {}'<\/span>.<\/span>format(1<\/span>))\n\n\nplt.<\/span>subplot(2<\/span>,2<\/span>,2<\/span>)\nplt.<\/span>plot(t, f2)\nplt.<\/span>title('N = {}'<\/span>.<\/span>format(2<\/span>))\n\n\nplt.<\/span>subplot(2<\/span>,2<\/span>,3<\/span>)\nplt.<\/span>plot(t,f3)\nplt.<\/span>title('N = {}'<\/span>.<\/span>format(3<\/span>))\n\n\nplt.<\/span>subplot(2<\/span>,2<\/span>,4<\/span>)\nplt.<\/span>plot(t, f4)\nplt.<\/span>title('N = {}'<\/span>.<\/span>format(4<\/span>))\n\nplt.<\/span>tight_layout()\nplt.<\/span>show()\n<\/pre>\n
     <\/p>\n
    The output of the code is given below:<\/p>\n
    \"\"<\/p>\n
     <\/p>\n
     <\/p>\n
    4. Working with Scatterplots<\/strong><\/h5>\n
    Scatterplots are used for a number of math applications. The code below shows a scatterplot. Most part of the code are explained as comments within the code.<\/p>\n
    # Working with Scatter Plot<\/span>\n\n# Set the number of dots in the plot<\/span>\nN =<\/span> 200<\/span>\n\n# Create a random x and y cordinates sampled uniformly from 0 to 1<\/span>\nx =<\/span> np.<\/span>random.<\/span>rand(N)\ny =<\/span> np.<\/span>random.<\/span>rand(N)\n\n# Create a random array sampled uniformly from [20, 120]<\/span>\n# 'size' array is used below to set the size of each dot<\/span>\nsize =<\/span> 100<\/span> *<\/span> np.<\/span>random.<\/span>rand(N) +<\/span> 20<\/span>\n\n# Create a rondom 4-tuples sampled uniformly from [0 to 1]<\/span>\n\n# The colors array is used to set the color of each dot<\/span>\ncolors =<\/span> np.<\/span>random.<\/span>rand(N,4<\/span>)\n\n# Create a figure that is of size 12 by 5 and create a scatter plot<\/span>\nplt.<\/span>figure(figsize=<\/span>(12<\/span>, 5<\/span>))\nplt.<\/span>scatter(x, y, c=<\/span>colors, s =<\/span> size)\nplt.<\/span>title('Scatter Plot'<\/span>)\nplt.<\/span>show()\n<\/pre>\n
     <\/p>\n
    The output of the scatter plot is shown below<\/p>\n
    \"\"<\/p>\n
     <\/p>\n
    5. Working with Histograms<\/strong><\/h5>\n
    A histogram is a diagram made up of rectangles placed side by side. The area of the rectangles are proportional to the frequency of a variable while the width is equal to the class interval.<\/p>\n
    The code below displays a histogram.<\/p>\n
    <\/p>\n
    # Working with Histograms<\/span>\nsamples =<\/span> np.<\/span>random.<\/span>randn(10000<\/span>)\nplt.<\/span>hist(samples, bins=<\/span>20<\/span>, \n         density=<\/span>True<\/span>, \n         alpha=<\/span>0.9<\/span>, \n         color=<\/span>(0.1<\/span>, 0.8<\/span>, 0.1<\/span>)\n        )\nplt.<\/span>title('Random Samples - Normal Distribution'<\/span>)\nplt.<\/span>ylabel('Frequency'<\/span>)\nplt.<\/span>xlabel('Samples'<\/span>)\n\n#Plot a red line<\/span>\nx =<\/span> np.<\/span>linspace(-<\/span>4<\/span>, 4<\/span>, 100<\/span>)\ny =<\/span> 1<\/span>\/<\/span>(2<\/span>*<\/span>np.<\/span>pi)**<\/span>0.5<\/span> *<\/span> np.<\/span>exp(-<\/span>x**<\/span>2<\/span>\/<\/span>2<\/span>)\nplt.<\/span>plot(x, y, 'r'<\/span>, alpha =<\/span> 0.8<\/span>)\nplt.<\/span>show()\n<\/pre>\n
     <\/p>\n
    The output of the histogram plot is given below<\/p>\n
    \"\"<\/p>\n
     <\/p>\n
    6. Creating a Bar Plot<\/strong><\/h5>\n
    A bar plot also called a bar graph or bar chart is used to present a categerical data with rectangular bars along with corresponding heights that is proportional to the values that they represent.<\/p>\n
    The code below creates a bar chart.<\/p>\n
    # Working With Bar Plots<\/span>\nmonths =<\/span> range<\/span>(1<\/span>,13<\/span>)\nprecipitation =<\/span> [88.8<\/span>,118.8<\/span>,201.0<\/span>,126.5<\/span>,102.2<\/span>,46.4<\/span>,40.8<\/span>,21.0<\/span>,29.4<\/span>,104.8<\/span>,192.0<\/span>,160.6<\/span>]\nplt.<\/span>bar(months,precipitation,edgecolor=<\/span>'red'<\/span>)\n\nplt.<\/span>xticks(months)\nplt.<\/span>yticks(range<\/span>(0<\/span>, 300<\/span>, 50<\/span>))\nplt.<\/span>grid(True<\/span>, alpha=<\/span>0.9<\/span>, \n         linestyle=<\/span>'--'<\/span>)\nplt.<\/span>title('Precipitation in Onitsha, 2015'<\/span>)\nplt.<\/span>ylabel('Total Precipitation (mm) '<\/span>)\nplt.<\/span>xlabel('Month'<\/span>)\n\nplt.<\/span>show()\n<\/pre>\n
     <\/p>\n
    The output of the code is given below:<\/p>\n
    \"\"<\/p>\n
    If you have come this far, you’ve done great. I recommend you do it over again with Part 1<\/a> so it becomes clearer.<\/p>\n
    Feel free to visit my Youtube channel<\/a> for more video lessons<\/p>\n","protected":false},"excerpt":{"rendered":"
    This is Part 2 of Plotting Tutorial in Python with Matplotlib.pyplot. You can find Part 1 here. Here, we cover the following Example 2 – … <\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"pagelayer_contact_templates":[],"_pagelayer_content":"","footnotes":""},"categories":[7],"tags":[],"class_list":["post-1941","post","type-post","status-publish","format-standard","hentry","category-python-tutorials"],"_links":{"self":[{"href":"https:\/\/kindsonthegenius.com\/blog\/wp-json\/wp\/v2\/posts\/1941","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/kindsonthegenius.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/kindsonthegenius.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/kindsonthegenius.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/kindsonthegenius.com\/blog\/wp-json\/wp\/v2\/comments?post=1941"}],"version-history":[{"count":1,"href":"https:\/\/kindsonthegenius.com\/blog\/wp-json\/wp\/v2\/posts\/1941\/revisions"}],"predecessor-version":[{"id":2109,"href":"https:\/\/kindsonthegenius.com\/blog\/wp-json\/wp\/v2\/posts\/1941\/revisions\/2109"}],"wp:attachment":[{"href":"https:\/\/kindsonthegenius.com\/blog\/wp-json\/wp\/v2\/media?parent=1941"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/kindsonthegenius.com\/blog\/wp-json\/wp\/v2\/categories?post=1941"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/kindsonthegenius.com\/blog\/wp-json\/wp\/v2\/tags?post=1941"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}