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.')