Practical_7: Matplotlib#
Exercise 1:#
Create a simple line plot for y = x for x values ranging from 0 to 10.
# Exercise 1
Exercise 2:#
Plot y = x^2 using Matplotlib for x values between -10 and 10.
# Exercise 2
Exercise 3:#
Create a scatter plot with 50 random points where x and y values are between 0 and 10.
# Exercise 3
Exercise 4:#
Plot a sine wave using Matplotlib for x values between 0 and 2π.
# Exercise 4
Exercise 5:#
Create a bar chart for the following data: categories = ['A', 'B', 'C', 'D'] and values = [3, 7, 5, 9].
# Exercise 5
Exercise 6:#
Create a histogram of 1000 random numbers generated from a normal distribution.
# Exercise 6
Exercise 7:#
Plot two line plots on the same graph: y1 = x^2 and y2 = x^3 for x ranging from 0 to 10.
# Exercise 7
Exercise 8:#
Add titles, axis labels, and a legend to the plot in Exercise 7.
# Exercise 8
Exercise 9:#
Create a subplot with 2 rows and 1 column. Plot y1 = x^2 in the first subplot and y2 = x^3 in the second.
# Exercise 9
Exercise 10:#
Use a different color and linestyle for each line in a plot of three functions: y1 = x, y2 = x^2, and y3 = x^3.
# Exercise 10
Exercise 11:#
Create a pie chart with 5 segments labeled A, B, C, D, and E, with values [25, 35, 20, 15, 5].
# Exercise 11
Exercise 12:#
Create a horizontal bar chart with categories = ['A', 'B', 'C', 'D'] and values = [3, 7, 5, 9].
# Exercise 12
Exercise 13:#
Change the figure size of a line plot to 10x6 inches.
# Exercise 13
Exercise 14:#
Plot a filled area under the curve of y = x^2 for x ranging from 0 to 10.
# Exercise 14
Exercise 15:#
Change the style of the plot to ggplot and replot the sine wave from Exercise 4.
# Exercise 15
Exercise 16:#
Create a stacked bar chart for the following data: Group A = [3, 5, 7], Group B = [2, 6, 4], and categories = ['X', 'Y', 'Z'].
# Exercise 16
Exercise 17:#
Create a plot with multiple subplots in a 2x2 grid. Plot y1 = x, y2 = x^2, y3 = x^3, and y4 = x^4.
# Exercise 17
Exercise 18:#
Create a heatmap using a 2D array of random values with shape (5, 5).
# Exercise 18
Exercise 19:#
Add error bars to a bar plot with categories = ['A', 'B', 'C', 'D'] and values = [3, 7, 5, 9], assuming the error is 1 for each value.
# Exercise 19
Exercise 20:#
Plot a sine wave using a dashed line and a cosine wave using a solid line on the same plot.
# Exercise 20
Exercise 21:#
Plot a contour plot for the function z = sin(x) + cos(y) over a grid of x and y values ranging from -5 to 5.
# Exercise 21
Exercise 22:#
Create a box plot for a dataset generated with 100 random numbers from a normal distribution.
# Exercise 22
Exercise 23:#
Create a scatter plot with a color map applied to the points, where the color represents the value of the points.
# Exercise 23
Exercise 24:#
Use Matplotlib to display an image from a file.
# Exercise 24
Exercise 25:#
Create a plot with logarithmic scaling on both axes.
# Exercise 25
Exercise 26:#
Create a 3D plot of the function z = x^2 + y^2 over a grid of x and y values.
# Exercise 26
Exercise 27:#
Create a radar chart with 5 variables and random values between 0 and 1.
# Exercise 27
Exercise 28:#
Create a violin plot to show the distribution of a dataset generated with 1000 random numbers from a normal distribution.
# Exercise 28
Exercise 29:#
Create a bar chart with different colors for each bar.
# Exercise 29
Exercise 30:#
Create a stem plot for the function y = sin(x) for x values between 0 and 2π.
# Exercise 30
Exercise 31:#
Create a scatter plot with markers of different sizes.
# Exercise 31
Exercise 32:#
Plot a cumulative histogram of 1000 random numbers generated from a uniform distribution.
# Exercise 32
Exercise 33:#
Create a pie chart with custom colors for each segment.
# Exercise 33
Exercise 34:#
Create a plot with twin y-axes where one axis represents y = x and the other represents y = x^2.
# Exercise 34
Exercise 35:#
Plot a density plot of 1000 random values from a normal distribution.
# Exercise 35
Exercise 36:#
Create a histogram and add a kernel density estimate (KDE) to the plot.
# Exercise 36
Exercise 37:#
Add gridlines to a line plot and change the color and linestyle of the grid.
# Exercise 37
Exercise 38:#
Create a bar chart with annotations showing the height of each bar above the bar.
# Exercise 38
Exercise 39:#
Create a filled contour plot for the function z = x^2 + y^2 over a grid of x and y values.
# Exercise 39
Exercise 40:#
Create a stacked area plot using three random datasets.
# Exercise 40
Exercise 41:#
Create a bar chart with error bars, where the error values are proportional to the bar values.
# Exercise 41
Exercise 42:#
Create a wind rose chart using random wind direction and speed data.
# Exercise 42
Exercise 43:#
Plot a cumulative frequency curve for a dataset of 100 random numbers.
# Exercise 43
Exercise 44:#
Create a waterfall chart using Matplotlib to show the changes in a sequence of values.
# Exercise 44
Exercise 45:#
Use the imshow function to display a 10x10 matrix of random values as an image.
# Exercise 45
Exercise 46:#
Create a line plot with different markers for each point.
# Exercise 46
Exercise 47:#
Create a time series plot using Matplotlib and plot random data over a range of dates.
# Exercise 47
Exercise 48:#
Create a bar chart with bars colored by category.
# Exercise 48
Exercise 49:#
Create a radar chart to visualize the strengths of five different attributes.
# Exercise 49
Exercise 50:#
Create a 3D scatter plot with random values for x, y, and z.
# Exercise 50