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![Matplotlib Line Plot
In this example, pyplot is imported as plt, and then used to plot three numbers in a straight line:
import matplotlib.pyplot as plt
# Plot some numbers:
plt.plot([1, 2, 3])
plt.title(”Line Plot”)
# Display the plot:
plt.show()
Figure. Line plot generated by Matplotlib:](https://image.slidesharecdn.com/visualizationandmatplotlibusingpython-230418052428-b7e21a1f/75/Visualization-and-Matplotlib-using-Python-pptx-19-2048.jpg)
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Visualization and Matplotlib using Python.pptx
- 1. Dr Sharmila SharadMore, Assistant Professor , Dept Of Science and Computer Science, MIT, ACSC,Alandi, Pune
- 2. Unit V: Matplotlib Introduction Installation Pyplot Plotting Markers Line Lables Grid Subplot Scatter Bars Histogram Pie chart
- 6. What Is MatplotlibIn Python? Matplotlib is a cross-platform, data visualization and graphical plotting library for Python and its numerical extension NumPy. As such, it offers a viable open source alternative to MATLAB.
- 8. The matplotlib scriptinglayer overlays two APIs: •The pyplot API is a hierarchy of Python code objects topped by matplotlib.pyplot •An OO (Object-Oriented) API collection of objects that can be assembled with greater flexibility than pyplot. This API provides direct access to Matplotlib’s backend layers. matplotlib.pyplot Installing Matplotlib Matplotlib and its dependencies can be downloaded as a binary (pre-compiled) package from the Python Package Index (PyPI), and installed with the following command: python -m pip install matplotlib
- 11. Matplotlib and Pyplotin Python The OO API and its interface is more customizable and powerful than pyplot, but considered more difficult to use……………so we use pyplot •matplotlib.pyplot.figure: Figure is the top-level container. It includes everything visualized in a plot including one or more Axes. •matplotlib.pyplot.axes: Axes contain most of the elements in a plot: Axis, Tick, Line2D, Text, etc., and sets the coordinates. It is the area in which data is plotted. Axes include the X- Axis, Y-Axis, and possibly a Z-Axis, as well. Display a plot in Python Matplotlib’s series of pyplot functions are used to visualize and decorate a plot.
- 12. How to Createa Simple Plot :- Plot() Function The matplotlib.pyplot.plot() function provides a unified interface for creating different types of plots. The simplest example uses the plot() function to plot values as x,y coordinates in a data plot. In this case, plot() takes 2 parameters for specifying plot coordinates: •Parameter for an array of X axis coordinates. •Parameter for an array of Y axis coordinates. Figure :- A simple plot created with the plot() function:
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- 15. How to CustomizePlot Appearance with Marker & Linestyle marker and linestyle are matplotlib keywords that can be used to customize the appearance of data in a plot without modifying data values. •marker is an argument used to label each data value in a plot with a ‘marker‘./Symbol •linestyle is an argument used to customize the appearance of lines between data values, or else remove them altogether. A partial list of string characters that are acceptable options for marker and linestyle: “-” solid line “--” dashed line style “ “ no line “o” letter marker
- 16. Matplotlib UI Menu Whenmatplotlib is used to create a plot, a User Interface (UI) and menu structure are generated. The UI can be used to customize the plot, as well as to pan/zoom and toggle various elements. Matplotlib and NumPy Numpy is a package for scientific computing. Numpy is a required dependency for matplotlib, which uses numpy functions for numerical data and multi-dimensional arrays
- 17. import numpy asnp import pandas as pd import matplotlib.pyplot as plt fig, ax = plt.subplots() # Hide axes without removing it: fig.patch.set_visible(False) ax.axis('off') ax.axis('tight') # Create a numpy random array in a pandas dataframe with 10 rows, 4 columns df = pd.DataFrame(np.random.randn(10, 4), columns=list('ABCD')) plt.title("Pandas Dataframe Plot") ax.table(cellText=df.values, colLabels=df.columns, loc='center') fig.tight_layout() plt.show() Matplotlib and Pandas Pandas is a library used by matplotlib mainly for data manipulation and analysis. Pandas provides an in- memory 2D data table object called a Dataframe. Unlike numpy, pandas is not a required dependency of matplotlib
- 18. Graphs and Charts •BarChart/Graph. •Pie Chart. •Line Graph or Chart. •Histogram Chart. •Area Chart. •Dot Graph or Plot. •Scatter Plot. •Bubble Chart.
- 19. Matplotlib Line Plot Inthis example, pyplot is imported as plt, and then used to plot three numbers in a straight line: import matplotlib.pyplot as plt # Plot some numbers: plt.plot([1, 2, 3]) plt.title(”Line Plot”) # Display the plot: plt.show() Figure. Line plot generated by Matplotlib:
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