Jul 5, 2016 · a = randi(50,1,200); b = randi(50,1,200); figure;scatter(a,b,'.') figure;plot(a,b,'.') When we run the following code , we receive exactly the same plots for a against b , my question is why should we even use or to rephrase again in what conditions scatter plot has advantage over plot function ? because plot seem to have more formatting ...

Jan 1, 2019 · I want to use Python's plt.scatter or ax.scatter to show a car finishing times as scatterplot chart. So my x axis contains an array: So my x axis contains an array: 'car001','car002','car003', ...

Jun 22, 2016 · I suggest bare plt.plot, plt.scatter in the context of an interactive session, possibly using IPython with its %matplotlib magic command, and also in the context of an exploratory Jupyter notebook. On the other hand the object oriented approach, plus a few plt convenience methods (2) , is the way to go

The first one is from matplotlib, the second one from pandas. They do the same, which is create a matplotlib scatter plot, but the matplotlib version returns a collection of points, whereas the pandas version returns a matplotlib subplot. This makes the matplotlib version a bit more versatile, as you can use the collection of points in another ...

I am trying to make a scatter plot and annotate data points with different numbers from a list. So, for example, I want to plot y vs x and annotate with corresponding numbers from n. y = [2.56422, 3.

Feb 27, 2013 · I have two lists, dates and values. I want to plot them using matplotlib. The following creates a scatter plot of my data. import matplotlib.pyplot as plt plt.scatter(dates,values) plt.show() plt.plot(dates, values) creates a line graph. But what I really want is a scatterplot where the points are connected by a line. Similar to in R:

Jul 13, 2019 · What is the difference between a "line" plot and a "scatter" plot when using DataFrame methods plot.line() and plot.scatter()? Obviously there are some superficial differences such as line plots being connected by default, but …

I'm new to visualization using matplotlib. I will like to make a plot of my machine learning model's predicted value vs the actual value. I made a prediction using random forest algorithm and will like to visualize the plot of true values and predicted values.

Jul 16, 2013 · import matplotlib.cm as cm plt.scatter(x, y, c=t, cmap=cm.cmap_name) Importing matplotlib.cm is optional as you can call colormaps as cmap="cmap_name" just as well. There is a reference page of colormaps showing what each looks like. Also know that you can reverse a colormap by simply calling it as cmap_name_r. So either

Aug 31, 2018 · import matplotlib.pyplot as plt import numpy as np import sklearn import sklearn.datasets import sklearn.linear_model import matplotlib %matplotlib inline matplotlib.rcParams['figure.figsize'] = (13.0, 9.0) # Generate a dataset and plot it np.random.seed(0) X, y = sklearn.datasets.make_moons(200, noise=0.55) print(y) plt.scatter(X[:,0], X[:,1 ...