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What is Matplotlib Pyplot?
- Introduction to pyplot# matplotlib.pyplot is a collection of functions that make matplotlib work like MATLAB. Each pyplot function makes some change to a figure: e.g., creates a figure, creates a plotting area in a figure, plots some lines in a plotting area, decorates the plot with labels, etc.
- Plotting with keyword strings# There are some instances where you have data in a format that lets you access particular variables with strings. For example, with structured arrays or pandas.DataFrame.
- Plotting with categorical variables# It is also possible to create a plot using categorical variables. Matplotlib allows you to pass categorical variables directly to many plotting functions.
- Controlling line properties# Lines have many attributes that you can set: linewidth, dash style, antialiased, etc; see matplotlib.lines.Line2D. There are several ways to set line properties.
- Plotting A Line
- Plotting Two Or More Lines on Same Plot
- Customization of Plots
- Plotting Matplotlibusing Bar Chart
- Plotting Matplotlibusing Histogram
- Plotting Matplotlibusing Scatter Plot
- Plotting Matplotlibusing Pie-Chart
- Plotting Curves of Given Equation
In this example, the code uses Matplotlib to create a simple line plot. It defines x and y values for data points, plots them using `plt.plot()`, and labels the x and y axes with `plt.xlabel()` and `plt.ylabel()`. The plot is titled “My first graph!” using `plt.title()`. Finally, the `plt.show()` function is used to display the graph with the speci...
In this example code uses Matplotlib to create a graph with two lines. It defines two sets of x and y values for each line and plots them using `plt.plot()`. The lines are labeled as “line 1” and “line 2” with `label` parameter. Axes are labeled with `plt.xlabel()` and `plt.ylabel()`, and the graph is titled “Two lines on the same graph!” with `plt...
In this example code uses Matplotlib to create a customized line plot. It defines x and y values, and the plot is styled with a green dashed line, a blue circular marker for each point, and a marker size of 12. The y-axis limits are set to 1 and 8, and the x-axis limits are set to 1 and 8 using `plt.ylim()` and `plt.xlim()`. Axes are labeled with `...
In this example code uses Matplotlib to create a bar chart. It defines x-coordinates (`left`), heights of bars (`height`), and labels for the bars (`tick_label`). The `plt.bar()` function is then used to plot the bar chart with specified parameters such as bar width, colors, and labels. Axes are labeled with `plt.xlabel()` and `plt.ylabel()`, and t...
In this example code uses Matplotlib to create a histogram. It defines a list of age frequencies (ages), sets the range of values from 0 to 100, and specifies the number of bins as 10. The plt.hist()function is then used to plot the histogram with the provided data and formatting, including the color, histogram type, and bar width. Axes are labeled...
In this example code uses Matplotlib to create a scatter plot. It defines x and y values and plots them as scatter points with green asterisk markers (`*`) of size 30. Axes are labeled with `plt.xlabel()` and `plt.ylabel()`, and the plot is titled “My scatter plot!” using `plt.title()`. The legend is displayed with the label “stars” using `plt.lege...
In this example code uses Matplotlib to create a pie chart. It defines labels for different activities (`activities`), the portion covered by each label (`slices`), and colors for each label (`colors`). The `plt.pie()` function is then used to plot the pie chart with various formatting options, including start angle, shadow, explosion for a specifi...
In this example code uses Matplotlib and NumPy to create a sine wave plot. It generates x-coordinates from 0 to 2π in increments of 0.1 using `np.arange()` and calculates the corresponding y-coordinates by taking the sine of each x-value using `np.sin()`. The points are then plotted using `plt.plot()`, resulting in a sine wave. Finally, the `plt.sh...
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Jan 4, 2022 · In this article, we will be learning about how to plot 2D data on 3D plot in Python. We will be demonstrating two methods in order to learn the concept. The first method will be using Matplotlib.pyplot.gca() function which is a pyplot module of the matplotlib library.
MethodDescriptionplot ()it creates the plot at the background of ...show ()it displays the created plotsxlabel ()it labels the x-axisylabel ()it labels the y-axisThe plot() function is used to draw points (markers) in a diagram. By default, the plot() function draws a line from point to point. The function takes parameters for specifying points in the diagram. Parameter 1 is an array containing the points on the x-axis.
Key concepts of matplotlib’s design. Understanding plt.subplots() Visualizing arrays with matplotlib. Plotting with the pandas + matplotlib combination. Free Bonus: Click here to download 5 Python + Matplotlib examples with full source code that you can use as a basis for making your own plots and graphics.
May 30, 2023 · This Matplotlib cheat sheet introduces you to the basics that you need to plot your data with Python and includes code samples.
It is the core object that contains the methods to create all sorts of charts and features in a plot. The %matplotlib inline is a jupyter notebook specific command that let’s you see the plots in the notbook itself.
