To group data by multiple columns in Pandas, you can use the groupby()
method and pass a list of column names. For example:
df.groupby(['column1', 'column2']).sum()
This will group the data in the DataFrame df
by the values in column1
and column2
, and then sum the values for each group.
To represent the grouped data in a bar graph, you can use the plot()
method with the kind='bar'
parameter. For example:
df.groupby(['column1', 'column2']).sum().plot(kind='bar')
This will generate a bar graph with the sum of the values for each group along the x-axis and the group labels along the y-axis. You can customize the graph further by adding labels, titles, and adjusting the size and layout.
Please start posting anonymously - your entry will be published after you log in or create a new account. This space is reserved only for answers. If you would like to engage in a discussion, please instead post a comment under the question or an answer that you would like to discuss
Asked: 2022-11-08 11:00:00 +0000
Seen: 11 times
Last updated: Nov 27 '22
What is the most efficient way to search through an acyclic graph?
How can an undirected graph be created in Gephi?
What is the way to view a DGML file that is very big in Visual Studio?
How can a horizontal line or band be included in jpGraph?
What is the longest route in a graph that has a specific direction and does not contain cycles?