How do I go about step 1?

import bokeh

import pandas as pd

from bokeh.plotting import figure

from bokeh.io import output_notebook, show

output_notebook()

df = pd.read_csv ( 'us.csv' )

print (df)

# not working df['total_vaccinations']= pd.to_daytime(df['total_vaccinations'])

#total_vaccinations x red bold

#people_fully_vaccinated y black

#filter data

#location

#California red

#Colorado green

#Texas blue

# (3) Include a ‘grey’ border around the visualization with line width of 8 and alpha value of 0.8

cal = df[df[ 'location' ] = = 'California' ]

cool = df[df[ 'location' ] = = 'Colorado' ]

tx = df[df[ 'location' ] = = 'Texas' ]

@TangentJ what is your actual question? There does not appear to be a question above. Also please edit your post to use block code formatting so that the code is intelligible (either with the </> icon on the editing toolbar, or triple backtick ``` fences around the code blocks)

Im trying to figure out how to make a graph with these modifications :

Create the following visualization (i.e. scatterplot) that shows the relationship between the total vaccinations (x axis) and people fully vaccinated (y axis) for the states of California, Colorado, and Texas.

I don’t know how to single out the three states from the rest.

I tried this
cal = df[df[ 'location' ] = = 'California' ]

cool = df[df[ 'location' ] = = 'Colorado' ]

tx = df[df[ 'location' ] = = 'Texas' ],
but my code will not work.

It’s a csv file with all the states from

USA COVID-19 Vaccinations | Kaggle

I just started with bokeh, jyputer and thonny this week, so all of this is very new to me.

Been doing some research, I think I found out what is wrong, this topic is what I was looking for, I didn’t know how to label the states on their axis.

Just FYI @TangentJ this is a support forum specifically for the Bokeh plotting library, but that question (how to take subsets of data from a dataframe) is a question about how to use Pandas. That would be better asked on Stack Overflow

Got ya. I kind of figured it out. I just need more practice, haha. Thanks for the info.