upxo.statops.distr_01 module

class upxo.statops.distr_01.distribution(data_name=None, data=None, nbins=[None], be_estimator='auto')[source]

Bases: object

RULES:: An instance should not store than more one data If data is updated, then update operations must be perfoemed
VARIABLES:: data_name: Data Name data: Data nbins: Number of bins hist: histograms bin_edges: edges of the bins
CONVENTIONS:: nbins: contained in a list H: contained in a list bin_edges: contained in a list

update_summary()[source]: Set or update te summary.

find_min()[source]: Find min.

find_mean()[source]: Find mean.

find_median(axis=None)[source]: Find median.

find_max()[source]: Find max.

find_total()[source]: Find total.

find_std_dev(axis=0)[source]: Find std dev.

find_skewness()[source]: Find skewness.

find_kurtosis()[source]: Find kurtosis.

find_variance(limits=None, inclusive=(True, True), axis=0)[source]: REF: https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.tvar.html#scipy.stats.tvar

find_percentiles(percentile_list=[0, 10, 50, 90, 100], throw_format='list', see=False)[source]: Find percentiles.

calc_histogram(be_estimator='auto')[source]

“be_estimator” options:

‘auto’
‘fd’ (Freedman Diaconis Estimator)
‘doane’
For more, refer: https://numpy.org/doc/stable/reference/generated/numpy.histogram_bin_edges.html

calc_rv_histogram()[source]: Return the rv histogram.

plot_histogram(be_estimator='auto')[source]: Visualise histogram using Matplotlib or PyVista.

class upxo.statops.distr_01.SUMMARY[source]

Bases: object

minimum = None

percentiles = None

maximum = None

total = None

mean = None

median = None

variance = None

skew = None

kurt = None

class upxo.statops.distr_01.KDE[source]

Bases: object

bw = None

kd = None

class upxo.statops.distr_01.HISTOGRAM[source]

Bases: object

hv = None

be = None

data = None

nbins = None