A line plot is a graph that shows the frequency of data along a number line. It is used to show continuous dataset. A line plot is used to visualise growth or decline in data over a time interval.
Program : Smile NGO has participated in a three week cultural mela. Using Pandas, they have stored the sales (in Rs) made day wise for every week in a CSV file named “MelaSales.csv”, as shown in Table.
Day-wise mela sales data
Depict the sales for the three weeks using a Line chart. It should have the following:
i. Chart title as “Mela Sales Report”.
ii. axis label as Days.
iii. axis label as “Sales in Rs”.
Line colours are red for week 1, blue for week 2 and brown for week 3.
import pandas as pd
import matplotlib.pyplot as plt
# reads "MelaSales.csv" to df by giving path to the file
df=pd.read_csv("MelaSales.csv")
#create a line plot of different color for each week
df.plot(kind='line', color=['red','blue','brown'])
# Set title to "Mela Sales Report"
plt.title('Mela Sales Report')
# Label x axis as "Days"
plt.xlabel('Days')
# Label y axis as "Sales in Rs"
plt.ylabel('Sales in Rs')
#Display the figure
plt.show()
The Figure displays a line plot as output for Program. Note that the legend is displayed by default associating the colours with the plotted data.
Line plot showing mela sales figures
The line plot takes a numeric value to display on the x axis and hence uses the index (row labels) of the DataFrame in the above example. Thus, x tick values are the index of the DataFramedf that contains data stored in MelaSales.CSV.
Customising Line Plot
We can substitute the ticks at x axis with a list of values of our choice by using plt.xticks(ticks,label) where ticks is a list of locations(locs) on x axis at which ticks should be placed, label is a list of items to place at the given ticks.
Program : Assuming the same CSV file, i.e., MelaSales. CSV, plot the line chart with following customisations:
Maker ="*"
Marker size=10
linestyle="--"
Linewidth =3
import pandas as pd
import matplotlib.pyplot as plt
df=pd.read_csv("MelaSales.csv")
#creates plot of different color for each week
df.plot(kind='line', color=['red','blue','brown'],marker="*",marke rsize=10,linewidth=3,linestyle="--")
plt.title('Mela Sales Report')
plt.xlabel('Days')
plt.ylabel('Sales in Rs')
#store converted index of DataFrame to a list
ticks = df.index.tolist()
#displays corresponding day on x axis
plt.xticks(ticks,df.Day)
plt.show()
Figure is generated as output of Program with xticks as Day names.
Mela sales figures with day names
