def histogram(x, data, color='red', bins=20, title=None, dropna=False):
'''Helper function to create a distribution histogram
for `npv.simulate`
'''
if dropna is True:
data.dropna(inplace=True)
ast.hist(data, data.columns[0], bins=bins)
def hist(self, bins=5):
'''HISTOGRAM PLOT VISUALIZATION'''
ast.hist(self.df, 'ad_total_twh', bins=bins, x_limit=None,
title='Online Advertising',
sub_title='Energy in TWh')
ast.hist(self.df, 'total_twh', bins=bins, x_limit=None,
title='Total Infrastructure',
sub_title='Energy in TWh')
def hist_full(df):
ast.hist(data=df,
x='A',
bins=40,
dropna=True,
vertical=True,
palette='colorblind',
style='fivethirtyeight',
dpi=240,
title='This is a title',
sub_title='And this a subtitle',
x_label='this is x label',
y_label='and this y',
legend=False,
x_scale='log',
x_limit=24)
def test_simple_minimal(df):
ast.corr(df)
ast.kde(data=df, x='A')
ast.hist(df, x='A')
ast.pie(df, x='other')
ast.swarm(df, x='A', y='B', hue='even')
ast.scat(df, x='A', y='B', hue='even')
ast.line(df, x='A')
ast.grid(df, x='A', y='B', col='even')
ast.box(df, x='odd', y='A', hue='even')
ast.violin(df, x='odd', y='A', hue='even')
ast.strip(df, x='odd', y='B', hue='even')
ast.count(df, x='cats')
ast.bargrid(df, x='even', y='B', hue='other', col='odd')
ast.overlap(df, x='A', y='B', label_col='other')
ast.multikde(df, x='A', label_col='even')
ast.compare(df, x='A', y=['B', 'C'], label_col='other')
ast.multicount(df, x='even', hue='odd', col='other')
def plot_hist(self, metric='val_acc', bins=10):
'''A histogram for a given metric
NOTE: remember to invoke %matplotlib inline if in notebook
metric :: the metric to correlate against
bins :: number of bins to use in histogram
'''
return hist(self.data, metric, bins=bins)
def plot_hist(self, metric, bins=10):
'''A histogram for a given metric
NOTE: remember to invoke %matplotlib inline if in notebook
metric | str | Column label for the metric to correlate with
bins | int | Number of bins to use in histogram
'''
try:
import astetik as ast
return ast.hist(self.data, metric, bins=bins)
except RuntimeError:
print('Matplotlib Runtime Error. Plots will not work.')
