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    which of the following is correct to import the matplotlib library import plt.matplotlib as plot import plot.matplotlib as pt import matplotlib.pt as plot import matplotlib.pyplot as plt

    Mohammed

    Guys, does anyone know the answer?

    get which of the following is correct to import the matplotlib library import plt.matplotlib as plot import plot.matplotlib as pt import matplotlib.pt as plot import matplotlib.pyplot as plt from screen.

    Pyplot tutorial — Matplotlib 2.0.2 documentation

    Pyplot tutorial

    matplotlib.pyplot is a collection of command style 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. In matplotlib.pyplot various states are preserved across function calls, so that it keeps track of things like the current figure and plotting area, and the plotting functions are directed to the current axes (please note that “axes” here and in most places in the documentation refers to the axes part of a figure and not the strict mathematical term for more than one axis).

    import matplotlib.pyplot as plt

    plt.plot([1,2,3,4])

    plt.ylabel('some numbers')

    plt.show()

    (Source code, png, pdf)

    You may be wondering why the x-axis ranges from 0-3 and the y-axis from 1-4. If you provide a single list or array to the plot() command, matplotlib assumes it is a sequence of y values, and automatically generates the x values for you. Since python ranges start with 0, the default x vector has the same length as y but starts with 0. Hence the x data are [0,1,2,3].

    plot() is a versatile command, and will take an arbitrary number of arguments. For example, to plot x versus y, you can issue the command:

    plt.plot([1, 2, 3, 4], [1, 4, 9, 16])

    For every x, y pair of arguments, there is an optional third argument which is the format string that indicates the color and line type of the plot. The letters and symbols of the format string are from MATLAB, and you concatenate a color string with a line style string. The default format string is ‘b-‘, which is a solid blue line. For example, to plot the above with red circles, you would issue

    import matplotlib.pyplot as plt

    plt.plot([1,2,3,4], [1,4,9,16], 'ro')

    plt.axis([0, 6, 0, 20])

    plt.show()

    (Source code, png, pdf)

    See the plot() documentation for a complete list of line styles and format strings. The axis() command in the example above takes a list of [xmin, xmax, ymin, ymax] and specifies the viewport of the axes.

    If matplotlib were limited to working with lists, it would be fairly useless for numeric processing. Generally, you will use numpy arrays. In fact, all sequences are converted to numpy arrays internally. The example below illustrates a plotting several lines with different format styles in one command using arrays.

    import numpy as np

    import matplotlib.pyplot as plt

    # evenly sampled time at 200ms intervals

    t = np.arange(0., 5., 0.2)

    # red dashes, blue squares and green triangles

    plt.plot(t, t, 'r--', t, t**2, 'bs', t, t**3, 'g^')

    plt.show()

    (Source code, png, pdf)

    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

    Use keyword args:

    plt.plot(x, y, linewidth=2.0)

    Use the setter methods of a Line2D instance. plot returns a list of Line2D objects; e.g., line1, line2 = plot(x1, y1, x2, y2). In the code below we will suppose that we have only one line so that the list returned is of length 1. We use tuple unpacking with line, to get the first element of that list:

    line, = plt.plot(x, y, '-')

    line.set_antialiased(False) # turn off antialising

    Use the setp() command. The example below uses a MATLAB-style command to set multiple properties on a list of lines. setp works transparently with a list of objects or a single object. You can either use python keyword arguments or MATLAB-style string/value pairs:

    lines = plt.plot(x1, y1, x2, y2)

    # use keyword args

    plt.setp(lines, color='r', linewidth=2.0)

    # or MATLAB style string value pairs

    plt.setp(lines, 'color', 'r', 'linewidth', 2.0)

    Here are the available Line2D properties.

    Property Value Type alpha float

    animated [True | False]

    antialiased or aa [True | False]

    clip_box a matplotlib.transform.Bbox instance

    clip_on [True | False]

    clip_path a Path instance and a Transform instance, a Patch

    color or c any matplotlib color

    contains the hit testing function

    dash_capstyle ['butt' | 'round' | 'projecting']

    dash_joinstyle ['miter' | 'round' | 'bevel']

    dashes sequence of on/off ink in points

    data (np.array xdata, np.array ydata)

    figure a matplotlib.figure.Figure instance

    label any string

    linestyle or ls [ '-' | '--' | '-.' | ':' | 'steps' | ...]

    linewidth or lw float value in points

    lod [True | False]

    marker [ '+' | ',' | '.' | '1' | '2' | '3' | '4' ]

    markeredgecolor or mec any matplotlib color

    markeredgewidth or mew float value in points

    markerfacecolor or mfc any matplotlib color

    markersize or ms float

    markevery [ None | integer | (startind, stride) ]

    picker used in interactive line selection

    pickradius the line pick selection radius

    solid_capstyle ['butt' | 'round' | 'projecting']

    स्रोत : matplotlib.org

    python

    from matplotlib import pyplot as plt import matplotlib.pyplot as plt Are the above statements equivalent? Which is more readable/better form?

    Is "from matplotlib import pyplot as plt" == "import matplotlib.pyplot as plt"?

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    Asked 7 years, 3 months ago

    Modified 6 months ago

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    from matplotlib import pyplot as plt

    import matplotlib.pyplot as plt

    Are the above statements equivalent? Which is more readable/better form?

    pythonmatplotlibpython-import

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    edited May 31, 2015 at 14:09

    Aleksandr Kovalev 3,2583 3 gold badges 33 33 silver badges 35 35 bronze badges

    asked May 31, 2015 at 13:37

    megashigger 8,27516 16 gold badges 45 45 silver badges 78 78 bronze badges Add a comment

    4 Answers

    39

    Even though they are equivalent, I think there is a pretty good argument that the second form import matplotlib.pyplot as plt is objectively more readable:

    It is generally customary to use import matplotlib.pyplot as plt and suggested in the matplotlib documentation (see http://matplotlib.org/users/pyplot_tutorial.html etc...) so this will be more familiar to most readers.

    import matplotlib.pyplot as plt is shorter but no less clear.

    import matplotlib.pyplot as plt gives an unfamiliar reader a hint that pyplot is a module, rather than a function which could be incorrectly assumed from the first form.

    Share Improve this answer

    answered May 31, 2015 at 13:57

    Eric Appelt 2,73313 13 silver badges 20 20 bronze badges 2

    Hey, I'm trying to get a hang of the terminology. Is "pyplot" alone the module and "matplotlib" also a module? Or is "matplotlib.pyplot" the module? Thanks! –

    megashigger

    Jun 1, 2015 at 12:48

    8

    matplotlib is a package, essentially a collection of related modules. At its simplest, a package can be just a directory containing the module files with an empty __init__.py file that tells python that the directory is to be treated as a package. A module B within package A (i.e. in the file structure A/B.py is imported as import A.B –

    Eric Appelt

    Jun 1, 2015 at 12:54

    @EricAppelt Is the syntax A.B the same with attributes of an object? –

    Anton

    Aug 8, 2021 at 12:25

    Add a comment 10

    They both work the same so it is up to you which you prefer, personally I don't like typing so I would prefer the second.

    from matplotlib import pyplot as plt

    import matplotlib.pyplot as plt1

    print(dir(plt) == dir(plt1))

    True Share Improve this answer

    edited May 31, 2015 at 13:44

    answered May 31, 2015 at 13:38

    Padraic Cunningham 171k22 22 gold badges 230 230 silver badges 313 313 bronze badges Add a comment 2

    Yes,Both are same. It's Depends upon you what you prefer to import.

    Personally I Like to Write :

    from matplotlib import pyplot as plt

    Because it's look more clear and clean to me.

    Share Improve this answer

    answered May 18, 2020 at 0:54

    Priya Bharti 211 1 bronze badge Add a comment 1

    Just noticed one case that makes the two statements work differently to me

    import matplotlib

    import matplotlib.pyplot as plt

    matplotlib.use('Qt5Agg')

    plt.plot(list(range(10)))

    The above code works well. But if I write the second line in the other way,

    import matplotlib

    from matplotlib import pyplot as plt

    matplotlib.use('Qt5Agg')

    plt.plot(list(range(10)))

    This above doensn't work and the process stops at "matplotlib.use('Qt5Agg')". Process finished with exit code -1073741571 (0xC00000FD)

    This happens in IDE like Spyder console or Pycharm console. I feel it's related to the backend used though I didn't have a clear clue.

    Share Improve this answer

    answered Mar 13 at 8:03

    Jason Choi 111 1 bronze badge Add a comment

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    First of all, make sure you have python and pip preinstalled on your system. To check Python version, type

    python --version

    To check pip version, type

    pip −V

    Then, run the following pip command in the command prompt to install Matplotlib.

    pip install matplotlib

    To verify that matplotlib is successfully installed on your system, execute the following command in the command prompt.

    import matplotlib

    matplotlib.__version__

    If matplotlib is successfully installed, the version of matplotlib will be displayed.

    Now, let us import Matplotlib and plot some random data points.

    Steps

    Import matplotlib.

    Set the figure size and adjust the padding between and around the subplots.

    Create random data points, x.

    Plot x using plot() method.

    To display the figure, use show() method.

    Example

    from matplotlib import pyplot as plt

    import numpy as np

    plt.rcParams["figure.figsize"] = [7.50, 3.50]

    plt.rcParams["figure.autolayout"] = True

    x = np.random.rand(20)

    plt.plot(x, '*-', color='red', markersize=10)

    plt.show()

    Output

    Rishikesh Kumar Rishi

    Updated on 09-Jun-2021 11:55:47

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    Mohammed 13 day ago
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    Guys, does anyone know the answer?

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