I am trying to plot a graph in python which would show me the occurrence of items over time. So I want to find out how many items that match two categories appear in each year and plot a graph based on these.

This is my data in excel:

What I want to end up with is a list of movies which are both fantasy and action and how many times they appear in every year. This is the end result which I have gotten to (which is correct)

i.e. there are 2 movies in 2004 which are both fantasy and action and there is one movie in 2005 which is both fantasy and action etc.

Here are the steps which I have taken to get to the result:

#import data:
data = pd.read_csv("data.csv")

#put all fantasy movies in a list:
fantasy_movies = data[['Name', 'Genre']][(data['Genre'] == 'Fantasy')]
fantasy_movies.rename(columns={'Genre' : 'Fantasy'}, inplace = True)

#put all action movies in a list:
action_movies = data[['Name', 'Genre']][(data['Genre'] == 'Action')]
action_movies.rename(columns={'Genre' : 'Action'}, inplace = True)

#merge the two datasets:
action_fantasy = pd.merge(fantasy_movies, action_movies)

#obtain a list of unique movie names:
unique = action_fantasy.Name.unique()

#make dates the column and unique names the rows
filter_data = data[(data.Name.isin(unique))] 
table = filter_data.pivot_table(filter_data, index = ['Name'],columns=['year'])

#replace all NaNs with zero
table1 = table.fillna(0)

#Count items in years
table1.gt(0).astype(int).sum(axis=0)

Now, from here I would like to do some kind of graph (I'm thinking of a bar graph) using Matplotlib that would have years on the bottom and going up by the amount as per the table1 result. I am struggling to create one, even though it should technically be as easy as putting data on the x column and data on the y column.

Like the code from W3 Schools:

matplotlib bar plot

If you really want to use

seaborn bar plot

Alternatively pass the DataFrame into