# Plotting a trend graph in Python

Last Updated : 21 Apr, 2021

Prerequisites: Matplotlib

A trend Graph is a graph that is used to show the trends data over a period of time. It describes a functional representation of two variables (x , y). In which the x is the time-dependent variable whereas y is the collected data.  The graph can be in shown any form that can be via line chart, Histograms, scatter plot, bar chart, and pie-chart. In python, we can plot these trend graphs by using matplotlib.pyplot library. It is used for plotting a figure for the given data.

The task is simple and straightforward, for plotting any graph we must suffice the basic data requirement after this determine the values of x over the period of time and data collected for y. Plot the graphs for the above-given data.

Given below are various implementations to depict the same:

Example 1:

## Python3

 `# import all the libraries ` `import` `numpy as np ` `import` `pandas as pd ` `import` `matplotlib.pyplot as plt ` ` `  `# create a dataframe ` `Sports ``=` `{ ` `    ``"medals"``: [``100``, ``98``, ``102``, ``56``, ``78``, ``56``, ``78``, ``96``], ` `    ``"Time_Period"``: [``2010``, ``2011``, ``2012``, ``2013``, ``2014``, ``2015``, ``2016``, ``2017``] ` `} ` ` `  `df ``=` `pd.DataFrame(Sports) ` `print``(df) ` ` `  `# to plot the graph ` `df.plot(x``=``"Time_Period"``, y``=``"medals"``, kind``=``"line"``) ` `plt.show() `

Output:

```   medals  Time_Period
0     100         2010
1      98         2011
2     102         2012
3      56         2013
4      78         2014
5      56         2015
6      78         2016
7      96         2017```

Example 2: Using the above data we would plot the scatter and bar graph.

## Python3

 `# import all the libraries ` `import` `numpy as np ` `import` `pandas as pd ` `import` `matplotlib.pyplot as plt ` ` `  `# create a dataframe ` `Sports ``=` `{ ` `    ``"medals"``: [``100``, ``98``, ``102``, ``56``, ``78``, ``56``, ` `               ``78``, ``96``], ` `   `  `    ``"Time_Period"``: [``2010``, ``2011``, ``2012``, ``2013``, ` `                    ``2014``, ``2015``, ``2016``, ``2017``] ` `} ` `df ``=` `pd.DataFrame(Sports) ` `print``(df) ` ` `  ` `  `# to plot the graph ` `# subplot (rowno,columno,position) is used ` `# to plot in a single frame. ` `# to plot the scatter graph ,write kind= scatter ` `df.plot(x``=``"Time_Period"``, y``=``"medals"``, kind``=``"scatter"``) ` `plt.title(``"scatter chart"``) ` `plt.subplot(``1``, ``1``, ``1``) ` ` `  ` `  `# to Plot the graph in Bar chart ` `df.plot(x``=``"Time_Period"``, y``=``"medals"``, kind``=``"bar"``) ` `plt.title(``"bar"``) ` `plt.subplot(``1``, ``1``, ``2``) ` ` `  `plt.show() `

Output:

Example 3: student getting marks in 2010.

## Python3

 `# import the library ` `import` `matplotlib.pyplot as plt ` ` `  ` `  `# Creation of Data ` `x1 ``=` `[``'math'``, ``'english'``, ``'science'``, ``'Hindi'``, ``'social studies'``] ` `y1 ``=` `[``92``, ``54``, ``63``, ``75``, ``53``] ` `y2 ``=` `[``86``, ``44``, ``65``, ``98``, ``85``] ` ` `  `# Plotting the Data ` `plt.plot(x1, y1, label``=``'Semester1'``) ` `plt.plot(x1, y2, label``=``'semester2'``) ` ` `  `plt.xlabel(``'subjects'``) ` `plt.ylabel(``'marks'``) ` `plt.title(``"marks obtained in 2010"``) ` ` `  `plt.plot(y1, ``'o:g'``, linestyle``=``'--'``, linewidth``=``'8'``) ` `plt.plot(y2, ``'o:g'``, linestyle``=``':'``, linewidth``=``'8'``) ` ` `  `plt.legend()`

Output:

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