How to plot pct_change for many stock names

I have a data set with prices of 6 major stocks i.e., Google, Amazon etc.

My plan is to create a plot which would show a percent change, pct_change()of column known as close_value.

As you can see my ticker_symbol is an object. I tried and changed it to float because of the string error but then I lost all ticker names i.e. I executed returns.close_value.plot();.

How not to lose stock names while plotting?

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Does this work?

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

# Create Sample DataFrame
df1 = pd.DataFrame({'day_date': ['2020-05-28', '2020-05-27', '2020-05-26', '2020-05-22'], 
                    'ticker_symbol': ['AAPL', 'AAPL','TSLA','TSLA'],
                    'close_value': [318, 400, 500, 450]})

# Convert to Timestamp format
df1['day_date'] = pd.to_datetime(df1['day_date'])

# Store % Change in new Column
df1['pct_change_close_value'] = df1['close_value'].pct_change()

# Fill null value with 0
df1['pct_change_close_value'].fillna(0, inplace = True)

# Display
display(df1)

# Check Data types of columns
display(df1.dtypes)

# Use Seaborn to plot
sns.lineplot(data = df1, x = 'day_date', y = 'pct_change_close_value', hue = 'ticker_symbol')

You just need to set hue = ticker_symbol in sns plot.