plt.figure(figsize=(8,5)) sns.scatterplot(data=df,x=’G’,y=’GA’) for i in range(df.shape): plt.text(x=df.G+0.3,y=df.GA+0.3,s=df.Team, fontdict=dict(color=’red’,size=10), bbox=dict(facecolor=’yellow’,alpha=0.5)) plt.xlim(df.G.min()-1,df.G.max()+1) #set x limit plt.ylim(df.GA.min()-1,df.GA.max()+1) #set y limit plt.title(“Goals Scored vs Conceded- Top 6 Teams”) #title plt.xlabel(“Goals Scored”) #x label plt.ylabel(“Goals Conceded”) #y label plt. In the below code you can see how I have applied a padding of 1 unit around the plot while setting x and y limits. I generally achieve this by increasing the plot area by using xlim() and ylim() functions in matplotlib. This can be done by changing the position, size etc. Removing axes spines sinplot() sns.despine() f, ax plt.subplots() sns.violinplot(datadata) sns.despine(offset10, trimTrue) sns.setstyle(whitegrid). It would be aesthetically more pleasing if the text could be wrapped within the plot’s canvas. However, we can observe that a few text boxes are jutting out of the figure area. We have completed constructing a labelled scatter plot. Scatter Plot with all labels (Image by author) Final Touch It can also be grouped within fontdict to make your code easy to read and understand. ![]() plt.text(df.G,df.GA,"TOT", color='red')Īdditional arguments like color, size, alpha(transperency) etc. x, y and s are positional arguments and need not be explicitly mentioned if their order is followed. He x and y are Goals scored and Goals conceded by TOT respectively. I can add the label using plt.text() Syntax: plt.text(x=x coordinate, y=y coordinate, s=string to be displayed) Coming to our dataset, I am a Totenham Hotspur(TOT) fan and am interested only in the performance of TOT against the other teams. It would be useful if USA’s and other selected competitors data is labelled so that we can understand how these countries are performing with respect to each other and rest of the world. For example, if we are examining a socio-economic statistic of USA, it makes no sense to display the labels of all countries in scatter plot. ![]() Labelling all the data points may render your plot too clunky and difficult to comprehend. I will try to help you as soon as possible.Most often scatter plots may contain large amount of data points, we might be interested how some specific items fare against the rest. However, if you have any doubts or questions, do let me know in the comment section below. Both cla() and clf() clears plot in Matplotlib. Similarly, the clf() function makes figure clear. The Matplotlib cla() function can be used as axes.clear() function. We have discussed both axes clearly and figure clear with examples and explanations. The clear() function as axes.clear() or figure.clear() clears the axes and figure of the plot, respectively. In this article, we have discussed ways of Matplotlib clear plot in Python. Numpy Axis in Python With Detailed Examples.Matplotlib Savefig() For Different Parameters in Python.How to Clear Python Shell in the Most Effective Way.Finally, the plt.show() statement gives the ‘ax’ figure and clears the ‘ax2’ figure with just its title. But since the ax2.clear() is used, the current ‘ax2’ figure plot is cleared except for its title. ![]() For the second figure, we plot it as per the given input values. But, we do not use the Matplotlib clear() function with the ‘ax’ plot. Also, the title of the figure is mentioned. The ylabel of figure 1 is ‘y-axis.’ The Matplotlib grid() is also ‘True,’ which returns grid lines for the figure. In the above example, the two plots ‘ax’ and ‘ax1’ are created.
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