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LaTeX ignores the spaces you type and uses spacing the way it's done in mathematics texts. You can use the following four commands in case you want a different spacing style\; – thick space\: – medium space\, – a thin space\! – a negative thin spaceTo remove random unwanted space in LaTeX-style maths in matplotlib plot, we can use "\!" which will reduce the extra spacing.Let's take an example and understand how it works. We will have two sub-plots and then we will add a complex mathematical equation (using LaTex) in a textbox in both the sub-plots. However, we will ... Read More
To get pixel coordinates for matplotlib-generated scatterplot, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Initialize a variable "n" to hold the number of sample data.Create a figure and a set of subplots.Make a scatter plot.Get the x and y data points using get_data() method.Get the pixel value of the plot.Get the pixel tranformed data.Get the figure width and height in points or pixelsPrint the x and y pixels value.To display the figure, use show() method.Exampleimport numpy as np import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = ... Read More
To animate text in matplotlib, we can take the following steps −Import "animation" package from matplotlib.Set the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure.Add an 'ax' to the figure as part of a subplot arrangement.Initialize a variable "text" to hold a string.Add text to the axes at x=0.20 and y=0.50.Make a list of colors.Make an animation by repeatedly calling a function *animate*, where size of text is increased and color is changed.To display the figure, use show() method.Examplefrom matplotlib import animation import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = ... Read More
To plot a rainbow circles in Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a figure and a set of subplots.Set the X and Y axes scale.Make a list of rainbow colors.Create a true circle at (0, 0).Add a circle instance 'c' to the figure.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 5.50] plt.rcParams["figure.autolayout"] = True fig, ax = plt.subplots() plt.axis("equal") ax.set(xlim=(-10, 10), ylim=(-10, 10)) for i in range(0, 7): rainbow = ['violet', 'indigo', 'blue', 'green', ... Read More
To plot thousands of circles quickly in Matplotlib, we will have to use matplotlib.collections. In this case, we will use CircleCollection.StepsImport the collections package from matplotlib along with pyplot and numpy.Set the figure size and adjust the padding between and around the subplots.Initialize variables "num" for number of small circles and "sizes" for sizes of circles.Create a list of circle patches.Add circle patch artist on the current axis.Set the margins of the axes.To display the figure, use show() method.Exampleimport numpy as np import matplotlib.pyplot as plt import matplotlib.collections as mc plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True num ... Read More
To plot multiple dataframes using Pandas functionality, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create two Pandas dataframes, df1 and df2, of two-dimensional, size-mutable, potentially heterogeneous tabular data.Plot df1 and df2 using plot() method.To display the figure, use show() method.Exampleimport pandas as pd from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True df1 = pd.DataFrame( dict( name=['John', 'James', 'Stephen', 'Kandy'], age=[23, 45, 12, 34] ) ... Read More
To plot a time series graph using Seaborn or Plotly, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a Pandas dataframe, df, to hold a date_time series "time" and another variable data, speed.Make a Seaborn line plot with the data, "time" and "speed"Rotate the tick params by 45.To display the figure, use show() method.Exampleimport seaborn as sns from matplotlib import pyplot as plt import pandas as pd import numpy as np plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True df = pd.DataFrame( dict( ... Read More
To draw a curve connecting two points instead of a straight line in matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Define a draw_curve() method to make a curve with a mathematical expression.Plot point1 and point2 data points.Plot x and y data points returned from the draw_curve() method.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True def draw_curve(p1, p2): a = (p2[1] - p1[1]) / (np.cosh(p2[0]) - np.cosh(p1[0])) b ... Read More
To make matplotlib date manipulation so that the year tick shows up every 12 months, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create d, y, s, years, months, monthsFmt and yearsFmt using Pandas, Numpy and matplotlib dates.Use "%B" in DateFormatter to show full month names.Ue "%Y" in DateFormatter to show years.Create a new figure or activate an existing figure.Add an 'ax' to the figure as part of a subplot arrangement.Plot "dts" and "s" data points using plot() method.Set minor or major axes locator and formatter. Set minor_locator as months ... Read More
To plot data from .txt file using matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Initialize empty lists for bar_names and bar_heights.Open a sample .txt file in read "r" mode and append to bar's name and height list.Make a bar plot.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True bar_names = [] bar_heights = [] for line in open("test_data.txt", "r"): bar_name, bar_height = line.split() bar_names.append(bar_name) bar_heights.append(bar_height) plt.bar(bar_names, bar_heights) plt.show()"test_data.txt" contains the following data −Javed ... Read More