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# which of the following is correct to import the matplotlib library 1 point import plt.matplotlib as plot import plot.matplotlib as pt import matplotlib.pt as plot import matplotlib.pyplot as plt

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### Mohammed

Guys, does anyone know the answer?

get which of the following is correct to import the matplotlib library 1 point 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.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

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"?

Asked 7 years, 3 months ago

Modified 6 months ago

Viewed 81k times 44

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

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.

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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

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.

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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.

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answered Mar 13 at 8:03

Jason Choi 111 1 bronze badge Add a comment

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Plot attribute missing from matplotlib

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स्रोत : stackoverflow.com

## Matplotlib Plotting with pyplot MCQ

This post contains 75 Python Matplotlib Plotting with pyplot MCQ. These Python Pyplot MCQ are handy for learning Python Data Visualization. ## Matplotlib Plotting with pyplot MCQ | Data Visualization MCQ

8 Comments / IP Class 12 MCQ, Matplotlib Pyplot / By Sanjay Kumar This post contains Multiple Choice based Questions with answers for Matplotlib Plotting with pyplot MCQ. These objective questions with answers are not only helpful for those students preparing for CBSE IP Class 12 Matplotlib Plotting with pyplot MCQ but also for all those students who are practicing and learning Python Programming specially Data Handling and Visualization using Python Matplotlib Plotting with pyplot .

You will get different categories of Questions for all the concept of Python Matplotlib Plotting with pyplot objective questions-

Assertion and Reason MCQs

Case Study Based MCQs

Find The Output Based MCQs

Concept Based MCQs Contents [hide]

1 Matplotlib Plotting with pyplot MCQ SET-1 (Q1-Q25)

2 Matplotlib Plotting with pyplot MCQ SET-2 (Q1-Q25)

3 Matplotlib Plotting with pyplot MCQ SET-3 (Q51-Q75)

4 MCQ of Class 12 IP (Informatics Practices)

### Matplotlib Plotting with pyplot MCQ SET-1 (Q1-Q25)

Which of the following does not visualize data?

a. Charts b. Maps c. Shapes d. Graphs Show Answer

Which of the following type of chart is not supported by pyplot?

a. Histogram b. Boxplot c. Pie d. All are correct Show Answer

In the given chart, box surrounded with red border is called a. Data series b. Chart Title c. Markers d. Legend Show Answer

To display histogram with well-defined edge we can write

a. df.plot( type = ‘hist’, edge = ‘red’)

b. df.plot( type = ‘hist’, edgecolor = ‘red’)

c. df.plot( type = ‘hist’, line = ‘red’)

d. df.plot(type = ‘hist’, linecolor = ‘red’)

plot which is used to given statistical summary is

a. Bar b. Line c. Histogram d. Box plot Show Answer

Which of the following is not the parameter of pyplot’s plot() method?

a. Marker b. Lineheight c. Linestyle d. Color Show Answer

To compare data we can use ____ chart

a. Line b. Bar c. Pie d. Scatter Show Answer

Which of the following chart element is used to identify data series by its color patterns?

a. Chart title b. Legend c. Marker d. Data labels Show Answer

Identify the following chart’s type a. Scatter Chart b. Bubble Chart c. Pie Chart

d. Frequency Polygon

Look at the following graph and select appropriate code to obtain this output. (Please assume that pandas and matplotlib is already imported) a. zone=[1,2,3,4]

schools = [230,430,300,140]

plt.plot(zone, school, ‘School Survey’)

plt.show() b. zone=[1,2,3,4]

schools = [230,430,300,140]

plt.plot(schools,zone, ‘School Survey’)

plt.show() c.  zone=[1,2,3,4]

schools = [230,430,300,140]

plt.plot(zone, school)

plt.title(“School Survey”)

plt.show() d. zone=[1,2,3,4]

schools = [230,430,300,140]

plt.plot(schools,zone)

plt.title(“School Survey”)

Which of the following is incorrect regarding Data Visualization?

a. Data visualization can be done using Matplotlib library in python.

b. Visualizing large and complex data does not produce effective results.

c. Data visualization is immensely useful in data analysis.

d. Decision makers use data visualization to understand business problems easily and build strategies.

Matplotlib is _____ plotting library

a. 1D b. 2D c. 3D d. All of above Show Answer

Data _____________ refers to graphical representation of data.consider the code given below:

a. Visualization b. Analysis c. Plotting d. Handling Show Answer

plt.bar(cities, population, color = [‘r’,’g’,’b’,’m’])

what will be color of last bar?

a. Magenta b. Green c. Blue d. Black Show Answer

Following chart is type of Raj has written following code to create a bar chart-

a. Line Chart b. Bar chart c. Histogram d. Scatter chart Show Answer

Import matplotlib.pyplot as plt

weekdays  = [‘sun’,’mon’,’tue’]

sale = [1234,3312,2541]

plt.bar(weekdays, sale)

स्रोत : techtipnow.in

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Mohammed 4 day ago

Guys, does anyone know the answer?