How to use is_datetime method in pandera

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date_utils.py

Source:date_utils.py

1# -*- coding: utf-8 -*-2import math3import calendar4from datetime import date, datetime, time5import pytz6from dateutil.relativedelta import relativedelta7from . import ustr8def get_month(date):9    ''' Compute the month dates range on which the 'date' parameter belongs to.10    :param date: A datetime.datetime or datetime.date object.11    :return: A tuple (date_from, date_to) having the same object type as the 'date' parameter.12    '''13    date_from = type(date)(date.year, date.month, 1)14    date_to = type(date)(date.year, date.month, calendar.monthrange(date.year, date.month)[1])15    return date_from, date_to16def get_quarter_number(date):17    ''' Get the number of the quarter on which the 'date' parameter belongs to.18    :param date: A datetime.datetime or datetime.date object.19    :return: A [1-4] integer.20    '''21    return math.ceil(date.month / 3)22def get_quarter(date):23    ''' Compute the quarter dates range on which the 'date' parameter belongs to.24    :param date: A datetime.datetime or datetime.date object.25    :return: A tuple (date_from, date_to) having the same object type as the 'date' parameter.26    '''27    quarter_number = get_quarter_number(date)28    month_from = ((quarter_number - 1) * 3) + 129    date_from = type(date)(date.year, month_from, 1)30    date_to = (date_from + relativedelta(months=2))31    date_to = date_to.replace(day=calendar.monthrange(date_to.year, date_to.month)[1])32    return date_from, date_to33def get_fiscal_year(date, day=31, month=12):34    ''' Compute the fiscal year dates range on which the 'date' parameter belongs to.35    A fiscal year is the period used by governments for accounting purposes and vary between countries.36    By default, calling this method with only one parameter gives the calendar year because the ending date of the37    fiscal year is set to the YYYY-12-31.38    :param date:    A datetime.datetime or datetime.date object.39    :param day:     The day of month the fiscal year ends.40    :param month:   The month of year the fiscal year ends.41    :return: A tuple (date_from, date_to) having the same object type as the 'date' parameter.42    '''43    max_day = calendar.monthrange(date.year, month)[1]44    date_to = type(date)(date.year, month, min(day, max_day))45    if date <= date_to:46        date_from = date_to - relativedelta(years=1)47        date_from += relativedelta(days=1)48    else:49        date_from = date_to + relativedelta(days=1)50        max_day = calendar.monthrange(date_to.year + 1, date_to.month)[1]51        date_to = type(date)(date.year + 1, month, min(day, max_day))52    return date_from, date_to53def start_of(value, granularity):54    """55    Get start of a time period from a date or a datetime.56    :param value: initial date or datetime.57    :param granularity: type of period in string, can be year, quarter, month, week, day or hour.58    :return: a date/datetime object corresponding to the start of the specified period.59    """60    is_datetime = isinstance(value, datetime)61    if granularity == "year":62        result = value.replace(month=1, day=1)63    elif granularity == "quarter":64        # Q1 = Jan 1st65        # Q2 = Apr 1st66        # Q3 = Jul 1st67        # Q4 = Oct 1st68        result = get_quarter(value)[0]69    elif granularity == "month":70        result = value.replace(day=1)71    elif granularity == 'week':72        # `calendar.weekday` uses ISO8601 for start of week reference, this means that73        # by default MONDAY is the first day of the week and SUNDAY is the last.74        result = value - relativedelta(days=calendar.weekday(value.year, value.month, value.day))75    elif granularity == "day":76        result = value77    elif granularity == "hour" and is_datetime:78        return datetime.combine(value, time.min).replace(hour=value.hour)79    elif is_datetime:80        raise ValueError(81            "Granularity must be year, quarter, month, week, day or hour for value %s" % value82        )83    else:84        raise ValueError(85            "Granularity must be year, quarter, month, week or day for value %s" % value86        )87    return datetime.combine(result, time.min) if is_datetime else result88def end_of(value, granularity):89    """90    Get end of a time period from a date or a datetime.91    :param value: initial date or datetime.92    :param granularity: Type of period in string, can be year, quarter, month, week, day or hour.93    :return: A date/datetime object corresponding to the start of the specified period.94    """95    is_datetime = isinstance(value, datetime)96    if granularity == "year":97        result = value.replace(month=12, day=31)98    elif granularity == "quarter":99        # Q1 = Mar 31st100        # Q2 = Jun 30th101        # Q3 = Sep 30th102        # Q4 = Dec 31st103        result = get_quarter(value)[1]104    elif granularity == "month":105        result = value + relativedelta(day=1, months=1, days=-1)106    elif granularity == 'week':107        # `calendar.weekday` uses ISO8601 for start of week reference, this means that108        # by default MONDAY is the first day of the week and SUNDAY is the last.109        result = value + relativedelta(days=6-calendar.weekday(value.year, value.month, value.day))110    elif granularity == "day":111        result = value112    elif granularity == "hour" and is_datetime:113        return datetime.combine(value, time.max).replace(hour=value.hour)114    elif is_datetime:115        raise ValueError(116            "Granularity must be year, quarter, month, week, day or hour for value %s" % value117        )118    else:119        raise ValueError(120            "Granularity must be year, quarter, month, week or day for value %s" % value121        )122    return datetime.combine(result, time.max) if is_datetime else result123def add(value, *args, **kwargs):124    """125    Return the sum of ``value`` and a :class:`relativedelta`.126    :param value: initial date or datetime.127    :param args: positional args to pass directly to :class:`relativedelta`.128    :param kwargs: keyword args to pass directly to :class:`relativedelta`.129    :return: the resulting date/datetime.130    """131    return value + relativedelta(*args, **kwargs)132def subtract(value, *args, **kwargs):133    """134    Return the difference between ``value`` and a :class:`relativedelta`.135    :param value: initial date or datetime.136    :param args: positional args to pass directly to :class:`relativedelta`.137    :param kwargs: keyword args to pass directly to :class:`relativedelta`.138    :return: the resulting date/datetime.139    """140    return value - relativedelta(*args, **kwargs)141def json_default(obj):142    """143    Properly serializes date and datetime objects.144    """145    from odoo import fields146    if isinstance(obj, date):147        if isinstance(obj, datetime):148            return fields.Datetime.to_string(obj)149        return fields.Date.to_string(obj)150    return ustr(obj)151def date_range(start, end, step=relativedelta(months=1)):152    """Date range generator with a step interval.153    :param start datetime: begining date of the range.154    :param end datetime: ending date of the range.155    :param step relativedelta: interval of the range.156    :return: a range of datetime from start to end.157    :rtype: Iterator[datetime]158    """159    are_naive = start.tzinfo is None and end.tzinfo is None160    are_utc = start.tzinfo == pytz.utc and end.tzinfo == pytz.utc161    # Cases with miscellenous timezone are more complexe because of DST.162    are_others = start.tzinfo and end.tzinfo and not are_utc163    if are_others:164        if start.tzinfo.zone != end.tzinfo.zone:165            raise ValueError("Timezones of start argument and end argument seem inconsistent")166    if not are_naive and not are_utc and not are_others:167        raise ValueError("Timezones of start argument and end argument mismatch")168    if start > end:169        raise ValueError("start > end, start date must be before end")170    if start == start + step:171        raise ValueError("Looks like step is null")172    if start.tzinfo:173        localize = start.tzinfo.localize174    else:175        localize = lambda dt: dt176    dt = start.replace(tzinfo=None)177    end = end.replace(tzinfo=None)178    while dt <= end:179        yield localize(dt)...

column_guesser.py

Source:column_guesser.py

1#-------------------------------------------------------------------------2# Copyright (c) Microsoft Corporation. All rights reserved.3# Licensed under the MIT License. See License.txt in the project root for4# license information.5#--------------------------------------------------------------------------6from datetime import timedelta, datetime7"""8Splits tabular data in the form of a list of rows into columns;9makes guesses about the role of each column for plotting purposes10(X values, Y values, and text labels).11"""12class Column(list):13    "Store a column of tabular data; record its name and whether it is numeric"14    # Object constructor15    def __init__(self, idx=None,name='', col=None, is_quantity=True, is_datetime=True, **kwargs):16        if col is not None:17            self.is_quantity = col.is_quantity18            self.is_datetime = col.is_datetime19            self.idx = col.idx20            self.name = col.name21        else:22            self.is_quantity = is_quantity23            self.is_datetime = is_datetime24            self.idx = idx25            self.name = name26        super(Column, self).__init__(**kwargs)27class ChartSubTable(dict):28    def __init__(self, col_x=None, col_y=None, name=None, mapping=None, **kwargs):29        self.col_x = col_x30        self.col_y = col_y31        self.name = name32        super(ChartSubTable, self).__init__(**kwargs)33        if mapping:34            self.update(mapping)35def is_quantity(val):36    """Is ``val`` a quantity (int, float, datetime, etc) (not str, bool)?37    38    Relies on presence of __sub__.39    """40    return hasattr(val, "__sub__")41class ColumnGuesserMixin(object):42    """43    plot: [x, y, y...], y44    pie: ... y45    """46    DATAFRAME_QUNATITY_TYPES = ["int64", "float64", "datetime64[ns]", "timedelta64[ns]", "int32",]47    DATAFRAME_TIME_TYPES = ["datetime64[ns]", "timedelta64[ns]",]48    def _build_chart_sub_tables(self, name=None, x_type='first'):49        self.chart_sub_tables = []50        self._build_columns(name, without_data=True)51        x_col_idx = None52        if x_type =='first':53            x_col_idx = 054        elif x_type == 'quantity':55            for idx,c in enumerate(self.columns):56                if c.is_quantity:57                    x_col_idx = idx58                    break59        elif x_type == 'datetime':60            for idx,c in enumerate(self.columns):61                if c.is_datetime:62                    x_col_idx = idx63                    break64        if x_col_idx is None:65            return66        quantity_columns = [c for idx,c in enumerate(self.columns) if idx != x_col_idx and c.is_quantity]67        non_quantity_columns = [c for idx,c in enumerate(self.columns) if idx != x_col_idx and not c.is_quantity]68        rows = self69        if self.columns[x_col_idx].is_quantity:70            rows = sorted(self, key=lambda row: row[x_col_idx])71        col_x = Column(col=self.columns[x_col_idx])72        for row in rows:73            if row[x_col_idx] not in col_x:74                col_x.append(row[x_col_idx])75        chart_sub_tables_dict = {}76        for row in rows:77            for qcol in quantity_columns:78                if len(non_quantity_columns) > 0:79                    sub_table_name = ':'.join([row[col.idx] for col in non_quantity_columns]) + ':' + qcol.name80                else:81                    sub_table_name =  qcol.name82                chart_sub_table = chart_sub_tables_dict.get(sub_table_name)83                if chart_sub_table is None:84                    chart_sub_table = chart_sub_tables_dict[sub_table_name] = ChartSubTable(85                        name=sub_table_name, 86                        col_x=Column(col=self.columns[x_col_idx]), 87                        col_y=Column(col=qcol),88                        mapping=dict(zip(col_x, [None for i in range(len(col_x))])))89                chart_sub_table[row[x_col_idx]] = row[qcol.idx]90        self.chart_sub_tables = list(chart_sub_tables_dict.values())91    def _build_columns(self, name=None, without_data=False):92        self.x = Column()93        self.ys = []94        rows = self95        if name:96            idx = self.columns_name.index(name)97            rows = sorted(self, key=lambda row: row[idx])  # sort by index98        self.columns = [Column(idx, name) for (idx, name) in enumerate(self.columns_name)]99        if len(self.columns_datafarme_type) > 0:100            for col in self.columns:101                datafarme_type = self.columns_datafarme_type[col.idx]102                col.is_quantity = datafarme_type in self.DATAFRAME_QUNATITY_TYPES103                col.is_datetime = datafarme_type in self.DATAFRAME_TIME_TYPES104            if without_data:105                return106        for row in rows:107            for (col_idx, col_val) in enumerate(row):108                col = self.columns[col_idx]109                if not without_data:110                    col.append(col_val)111                if len(self.columns_datafarme_type) == 0:112                    if (col_val is not None) and (not is_quantity(col_val)):113                        col.is_quantity = False114                        col.is_datetime = False115                    elif not isinstance(col_val, datetime):116                        col.is_datetime = False117    def _get_y(self):118        for idx in range(len(self.columns) - 1, -1, -1):119            if self.columns[idx].is_quantity:120                self.ys.insert(0, self.columns.pop(idx))121                return True122    def _get_x(self):123        for idx in range(len(self.columns)):124            if self.columns[idx].is_quantity:125                self.x = self.columns.pop(idx)126                return True127    def _get_xlabel(self, xlabel_sep=" "):128        self.xlabels = []129        if self.columns:130            for row_idx in range(len(self.columns[0])):131                self.xlabels.append(xlabel_sep.join(str(c[row_idx]) for c in self.columns))132        self.xlabel = ", ".join(c.name for c in self.columns)133    def _get_xlabel(self, xlabel_sep=" ", index=None):134        self.xlabels = []135        if self.columns:136            for row_idx in range(len(self.columns[0])):137                self.xlabels.append(xlabel_sep.join(str(c[row_idx]) for c in self.columns))138        self.xlabel = ", ".join(c.name for c in self.columns)139    def _guess_columns(self):140        self._build_columns()141        self._get_y()142        if not self.ys:143            raise AttributeError("No quantitative columns found for chart")144    def build_columns(self, name=None):145        """146        just build the columns.147        if name specified, first sort row by name148        """149        self._build_columns(name)150    def guess_pie_columns(self, xlabel_sep=" "):151        """152        Assigns x, y, and x labels from the data set for a pie chart.153        154        Pie charts simply use the last quantity column as 155        the pie slice size, and everything else as the156        pie slice labels.157        """158        self._guess_columns()159        self._get_xlabel(xlabel_sep)160    def guess_plot_columns(self):161        """162        Assigns ``x`` and ``y`` series from the data set for a plot.163        164        Plots use:165          the rightmost quantity column as a Y series166          optionally, the leftmost quantity column as the X series167          any other quantity columns as additional Y series168        """169        self._guess_columns()170        self._get_x()171        while self._get_y():...

test_utils.py

Source:test_utils.py

1"""Tests for the sdv.constraints.utils module."""2from datetime import datetime3import pandas as pd4from sdv.constraints.utils import is_datetime_type5def test_is_datetime_type_with_datetime_series():6    """Test the ``is_datetime_type`` function when a datetime series is passed.7    Expect to return True when a datetime series is passed.8    Input:9    - A pandas.Series of type `datetime64[ns]`10    Output:11    - True12    """13    # Setup14    data = pd.Series([15        pd.to_datetime('2020-01-01'),16        pd.to_datetime('2020-01-02'),17        pd.to_datetime('2020-01-03')],18    )19    # Run20    is_datetime = is_datetime_type(data)21    # Assert22    assert is_datetime23def test_is_datetime_type_with_datetime():24    """Test the ``is_datetime_type`` function when a datetime is passed.25    Expect to return True when a datetime variable is passed.26    Input:27    - datetime.Datetime28    Output:29    - True30    """31    # Setup32    data = datetime(2020, 1, 1)33    # Run34    is_datetime = is_datetime_type(data)35    # Assert36    assert is_datetime37def test_is_datetime_type_with_pandas_datetime():38    """Test the ``is_datetime_type`` function when a pandas.datetime is passed.39    Expect to return True when a datetime variable is passed.40    Input:41    - pandas.Datetime42    Output:43    - True44    """45    # Setup46    data = pd.to_datetime('2020-01-01')47    # Run48    is_datetime = is_datetime_type(data)49    # Assert50    assert is_datetime51def test_is_datetime_type_with_int():52    """Test the ``is_datetime_type`` function when an int is passed.53    Expect to return False when an int variable is passed.54    Input:55    - int56    Output:57    - False58    """59    # Setup60    data = 261    # Run62    is_datetime = is_datetime_type(data)63    # Assert64    assert is_datetime is False65def test_is_datetime_type_with_string():66    """Test the ``is_datetime_type`` function when a string is passed.67    Expect to return False when a string variable is passed.68    Input:69    - string70    Output:71    - False72    """73    # Setup74    data = 'test'75    # Run76    is_datetime = is_datetime_type(data)77    # Assert78    assert is_datetime is False79def test_is_datetime_type_with_int_series():80    """Test the ``is_datetime_type`` function when an int series is passed.81    Expect to return False when an int series variable is passed.82    Input:83    -  pd.Series of type int84    Output:85    - False86    """87    # Setup88    data = pd.Series([1, 2, 3, 4])89    # Run90    is_datetime = is_datetime_type(data)91    # Assert...

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