Line plots with plot() in Pandas - Step-by-Step Execution

Concept Flow - Line plots with plot()

Start with DataFrame

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Call df.plot()

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Plot function reads data

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Draw line plot

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Show plot on screen

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End

The flow starts with a DataFrame, calls the plot() method, which reads the data and draws a line plot, then shows it on screen.

Execution Sample

Pandas

import pandas as pd
import matplotlib.pyplot as plt

data = {'Year': [2018, 2019, 2020, 2021], 'Sales': [250, 300, 400, 350]}
df = pd.DataFrame(data)
df.plot(x='Year', y='Sales')
plt.show()

This code creates a DataFrame with sales data over years and plots a line graph of Sales vs Year.

Execution Table

Step	Action	Data Read	Plotting Action	Output
1	Create DataFrame	{'Year':[2018,2019,2020,2021],'Sales':[250,300,400,350]}	None	DataFrame with 4 rows created
2	Call df.plot(x='Year', y='Sales')	Columns 'Year' and 'Sales'	Prepare line plot axes and lines	Plot object created but not shown
3	Call plt.show()	None	Render plot window	Line plot displayed with Year on x-axis and Sales on y-axis
4	End	None	None	Plot window remains until closed

💡 Plot is shown and program waits until user closes the plot window

Variable Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	Final
data	{'Year':[2018,2019,2020,2021],'Sales':[250,300,400,350]}	Same	Same	Same	Same
df	None	DataFrame with 4 rows	Same	Same	Same
plot_object	None	Line plot object created	Same	Same	Same

Key Moments - 2 Insights

Why does the plot not show immediately after calling df.plot()?

Calling df.plot() creates the plot object but does not display it. The plot appears only after plt.show() is called, as shown in execution_table step 3.

What does the x='Year' and y='Sales' mean in df.plot()?

They tell pandas which columns to use for the x-axis and y-axis. This is shown in execution_table step 2 where these columns are read for plotting.

Visual Quiz - 3 Questions

Look at the execution table, what is the output after step 2?

A Line plot displayed

B DataFrame created

C Plot object created but not shown

D Plot window closed

💡 Hint

Check the 'Output' column in execution_table row with Step 2

At which step is the plot actually displayed on screen?

A Step 1

B Step 3

C Step 2

D Step 4

💡 Hint

Look at the 'Plotting Action' and 'Output' columns in execution_table

If we omit plt.show(), what happens according to the execution flow?

A Plot is created but not displayed

B Plot is created and displayed automatically

C DataFrame is not created

D Error occurs

💡 Hint

Refer to key_moments about when the plot shows and execution_table step 3

Concept Snapshot

Use df.plot(x='col1', y='col2') to create a line plot.
The x and y specify columns for axes.
Call plt.show() to display the plot.
Plotting reads data, draws lines, then shows.
Without plt.show(), plot is not visible.

Full Transcript

We start with a DataFrame containing data. Calling df.plot() reads the specified columns and prepares a line plot object. However, the plot does not appear until plt.show() is called, which renders the plot window on screen. Variables like the DataFrame and plot object remain unchanged after creation. Beginners often wonder why the plot is not visible immediately after df.plot(); this is because plt.show() triggers the display. The x and y parameters tell pandas which columns to use for the axes. If plt.show() is omitted, the plot is created but not shown. This step-by-step flow helps understand how line plots are made and displayed using pandas and matplotlib.