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How to use rps_series_to_df method in yandex-tank

Best Python code snippet using yandex-tank

plugin.py

Source:plugin.py

...227        except Exception:228            logger.warning('Failed to parse stpd file')229            logger.debug('', exc_info=True)230            return pandas.DataFrame()231        return self.rps_series_to_df(pandas.Series(rows_list))232    def count_actual_rps(self, data, last_piece):233        """ Counts actual rps on base of input chunk. Uses buffer for latest timestamp in df. """234        if not last_piece and not data.empty:235            concat_ts = pandas.concat([(data.ts / 1e6).astype(int), self.rps_metrics['actual_rps_latest']])236            self.rps_metrics['actual_rps_latest'] = concat_ts.loc[lambda s: s == concat_ts.max()]237            series_to_send = concat_ts.loc[lambda s: s < concat_ts.max()]238            df = self.rps_series_to_df(series_to_send) if series_to_send.any else pandas.DataFrame([])239        else:240            df = self.rps_series_to_df(self.rps_metrics['actual_rps_latest'])241            self.rps_metrics['actual_rps_latest'] = pandas.Series()242        return df243    @staticmethod244    def monitoring_data_to_dfs(data):245        panels = {}246        for chunk in data:247            for panel_name, content in chunk['data'].items():248                if panel_name in panels:249                    for metric_name, value in content['metrics'].items():250                        if metric_name in panels[panel_name]:251                            panels[panel_name][metric_name]['value'].append(value)252                            panels[panel_name][metric_name]['ts'].append(chunk['timestamp'])253                        else:254                            panels[panel_name][metric_name] = {'value': [value], 'ts': [chunk['timestamp']]}255                else:256                    panels[panel_name] = {name: {'value': [value], 'ts': [chunk['timestamp']]} for name, value in content['metrics'].items()}257        return {'{}:{}'.format(panelk, name): pandas.DataFrame({'ts': [ts * 1000000 for ts in values['ts']], 'value': values['value']})258                for panelk, panelv in panels.items() for name, values in panelv.items()}259    @staticmethod260    def rps_series_to_df(series):261        df = series.value_counts().to_frame(name='value')262        df_to_send = df.rename_axis('ts')263        df_to_send.reset_index(inplace=True)264        df_to_send.loc[:, 'ts'] = (df_to_send['ts'] * 1e6).astype(int)265        return df_to_send266    @staticmethod267    def filter_df_by_case(df, case):268        """269        Filter dataframe by case name. If case is '__overall__', return all rows.270        :param df: DataFrame271        :param case: str with case name272        :return: DataFrame with columns 'ts' and 'value'273        """274        case = case.strip()...

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