Pandas can not plot the same data on both x and y

I want to plot y_1 on x and y_1 on y axis for being ideal line but there is an error.

The following is my code,

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np

def plot_me():
       df = pd.DataFrame({
        'y_1': [20, 30, 290, 675, 800],
        'y_2': [22, 25, 281, 600, 900]
        }, index=[1990, 1997, 2003, 2009, 2014])
   
    df.plot.line(x='y_1', y='y_2')    
    df.plot.line(x='y_1', y='y_1')
    plt.show()

plot_me()

File "/home/MyUser/.local/lib/python3.9/site-packages/pandas/core/indexes/base.py", line 3623, in get_loc raise KeyError(key) from err

However, this works if I change to,
df.plot.scatter(x='y_1', y='y_1')

df.plot.scatter(x='y_1', y='y_1')
and it works

This is because of df.plot.line() doesn't accept the same input for both parameters. As per the docs:

> x: label or position, optional
Allows plotting of one column versus another. If not specified, the index of the DataFrame is used.

> y: label or position, optional
Allows plotting of one column versus another. If not specified, all numerical columns are used.

With the key word here being another. In contrast, df.plot.scatter() doesn't mention this:

>x: int or str
The column name or column position to be used as horizontal coordinates for each point.

EDIT: Based on your comment, copying the column into a new one, does work:

def plot_me():
       df = pd.DataFrame({
        'y_1': [20, 30, 290, 675, 800],
        'y_2': [22, 25, 281, 600, 900]
        }, index=[1990, 1997, 2003, 2009, 2014])
       df['y_test'] = df['y_1']
       df.plot.line(x='y_1', y='y_2')    
       df.plot.line(x='y_1', y='y_test')
       plt.show()

plot_me()

Showing:

Pandas' plotting functionality does not support plotting the same data on both the x-axis and y-axis directly. The reason for this limitation is that pandas' plotting methods are primarily designed for visualizing relationships between different columns or variables in a DataFrame.

If you want to plot the same data on both the x-axis and y-axis, you can use matplotlib directly to achieve this. Here's an example of how you can modify the code to plot the same data on both axes using matplotlib:

import pandas as pd
import matplotlib.pyplot as plt

def plot_me():
    df = pd.DataFrame({
        'y_1': [20, 30, 290, 675, 800],
        'y_2': [22, 25, 281, 600, 900]
    }, index=[1990, 1997, 2003, 2009, 2014])

    fig, ax = plt.subplots()
    ax.plot(df['y_1'], df['y_1'], label='y_1')
    ax.set_xlabel('y_1')
    ax.set_ylabel('y_1')
    ax.legend()
    plt.show()

plot_me()




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