i am trying to get a bokeh server to run, but when i type in the command in my terminal i get an error message - server

Question

I am trying to run the code below in a bokeh server to visualize the plots. the final_imdb_dataframe is in the same directory as the python code. these are the steps i take to get the server to run:
open my terminal
type in "cd" then a space and then my directory in for the map containing my python script and the final_imdb_dataframe
press enter
type: bokeh serve --show "filename.py"
press enter
in my terminal i am getting this error message however:
bokeh : The term 'bokeh' is not recognized as the name of a cmdlet, function, script file, or operable program. (the complete error message is attached as a picture)
when i type in "pip show bokeh" in the command promt in python it gives me this:
pip show bokeh
Name: bokeh
Version: 2.4.3
Summary: Interactive plots and applications in the browser from Python
Home-page: https://github.com/bokeh/bokeh
Author: Bokeh Team
Author-email: info#bokeh.org
License: BSD-3-Clause
Location: c:\users\fazan\anaconda\lib\site-packages
Requires: Jinja2, numpy, packaging, pillow, PyYAML, tornado, typing-extensions
Required-by: hvplot, panel
Note: you may need to restart the kernel to use updated packages.
so it should work right?
i don't know what to do anymore...
code:
import pandas as pd
from bokeh.plotting import figure, show
import numpy as np
from bokeh.models import ColumnDataSource, HoverTool, Slider, RangeSlider, Div, Select
from bokeh.io import output_file, curdoc
from bokeh.layouts import column, row, layout
#EERSTE PLOT:
#line diagram of amount of movies released each year en avg rating displayed over the years
df = pd.read_csv("final_imdb_dataframe")
#"unnamed column weghalen
df.drop(df.columns[df.columns.str.contains('unnamed',case = False)],axis = 1, inplace = True)
#creating plot 2
plot2 = figure(plot_width = 1000,
plot_height = 400,
x_axis_label= "year",
title = "watchtime and movie rating over the years")
#creating a dropdown menu
source2 = ColumnDataSource(data={'x': df["release_date"], 'y': df["watchtime"]})
plot2.circle(x="x", y="y", size = 3, source = source2, alpha = 0.2)
def update_plot(attr, old, new):
if new == 'watchtime':
source2.data = {'x' : df["release_date"], 'y' : df["watchtime"]}
else:
source2.data = {'x' : df["release_date"], 'y' : df["movie_rating"]}
select = Select(title = "keuze menu", options=["watchtime", "movie_rating"], value = 'watchtime')
#code for updating the plot when the value is changed
select.on_change('value', update_plot)
#TWEEDE PLOT:
#creating a list of all the years a movie came out
dfrelease = df.release_date.drop_duplicates().tolist()
#sorting the list with release dates to get them in chronological order
dfrelease1 = sorted(dfrelease)
#creating an empty list
total_releases_per_year = []
#adding the amount of movies that came out every year to the list
for i in range(len(dfrelease1)):
total_releases_per_year.append(len(df[df["release_date"] == dfrelease1[i]]))
#creating a columndatasource of the two lists created above to make it possible for the hovertool to be used
source1 = ColumnDataSource(data=dict(year = dfrelease1, amount_of_movies_made = total_releases_per_year))
#making a hovertool
hover2 = HoverTool(tooltips=[("year", "#year"), ("amount of movies made", "#amount_of_movies_made")])
#creating plot 3
plot3 = figure(plot_width = 1000,
plot_height = 400,
x_axis_label= "year",
y_axis_label = "amount of movies",
title = "amount of movies per year")
plot3.line("year", "amount_of_movies_made", source = source1)
plot3.add_tools(hover2)
#DERDE PLOT:
#creating the ColumnDataSource
df_sel = df[df["release_date"] == 2020]
source1 = ColumnDataSource(df_sel)
#scatter plot
p1 = figure(title = "relation 'watchtime' and 'movie rating' over the years",
x_axis_label= "watchtime",
y_axis_label= "rating (0-10)",
plot_width = 1000,
plot_height = 400)
p1.circle(x="watchtime", y="movie_rating", alpha = 0.2, source=source1)
#making the rangeslider
slider = RangeSlider(title="release date", value= (1919, 2021), start=1919, end=2020, step=1)
#making the hover tool
hover1 = HoverTool(tooltips=[("title", "#movie_name"),("gross", "#gross_collection"),("votes", "#votes"),("genre", "#genre"), ("watchtime", "#watchtime"),("rating", "#movie_rating"),("release date", "#release_date")])
#making a def callback for the rangeslider to work when moved
def callback(attr, old, new):
year = slider.value
source1.data = df[(df["release_date"] >= year[0]) & (df["release_date"] <= year[1])]
slider.on_change("value", callback)
layout = column(slider, p1) #create a layout with slider on top of plot
p1.add_tools(hover1) #adding hover tool
layout3 = column(select, plot2, plot3, slider, p1) #making the layout for the dashboard
curdoc().add_root(layout3)*
i tried what i wrote above and expected acces to the bokeh server that would show me my plots. i have done this before on my previous computer (mac) and it worked then. now on my lenovo it is not working.`