如何在python中处理数据矩阵？

Question

I'd like to create code that can read create a histogram from a matrix of data that contains information about movies. The data set (matrix) contains several columns, and I'm interested in the column that contains movie release years and another column that says whether or not they pass the bechtel test (the data set defines "Pass" and "Fail" as indicators of whether a movie passed or failed the test). Knowing the nth column number of these two columns (release year and pass/fail), how can I create a histogram of the movies that fail the test, with the x axis containing bins of movie years? The bin sizes are not too important, whatever pyplot defaults to would be fine.

What I can do (which is not a lot) is this:

plt.hist(year_by_Test_binary[:,0])

which creates a pretty but meaningless histogram of how many movies were released in bins of years (the matrix has years in the 0th column).

If you couldn't already tell, I am python-illiterate and struggling. Any help would be appreciated.

Answer 1

Assuming n is the column of the Bechdel test, and that your data is numpy like:

plt.hist([matrix[matrix[:,n] == 'Pass', 0], matrix[matrix[:,n] == 'Fail', 0]])

We're giving numpy two vectors of years, one with movies passing and one with movies failing. It will then create two histograms for each category, so you can visually identify changes to the categories.

Answer 2

for to convert a data to an matrix use :

numpy.asarray(data)

and to present in a histogram you can use :

plt.plot(data)

or

plt.hist(data, bins)

bins is the niveau of your data