AI/ML perfplot for performance Plotting

AI/ML perfplot for performance Plotting 

perfplot extends Python's timeit by testing snippets with input parameters (e.g., the size of an array) and plotting the results. This has also option for live update to the ui.

The code is like below 

import perfplot, string

np.random.seed(123)

def shape(df):

    return df[df.education == 'a'].shape[0]

def len_df(df):

    return len(df[df['education'] == 'a'])

def query_count(df):

    return df.query('education == "a"').education.count()

def sum_mask(df):

    return (df.education == 'a').sum()

def sum_mask_numpy(df):

    return (df.education.values == 'a').sum()

def make_df(n):

    L = list(string.ascii_letters)

    df = pd.DataFrame(np.random.choice(L, size=n), columns=['education'])

    return df

perfplot.show(

    setup=make_df,

    kernels=[shape, len_df, query_count, sum_mask, sum_mask_numpy],

    n_range=[2**k for k in range(2, 25)],

    logx=True,

    logy=True,

    equality_check=False, 

    xlabel='len(df)')

References:

https://stackoverflow.com/questions/35277075/python-pandas-counting-the-occurrences-of-a-specific-value

https://pypi.org/project/perfplot/