frequencies.pyc
1 o 2 e��cL � @ s� d dl mZ d dlZd dlZd dlmZ d dlmZm Z m 3 Z 4 m Z d dl m Z mZmZmZmZ d dlmZmZ d dlmZmZmZmZmZ d dlm Z d d l m Z d d 5 l m Z d d l!m"Z" d d l#m$Z$m%Z%m&Z& d d l'm(Z(m)Z) d dl*m+Z+ i dd�dd�dd�dd�dd�dd�dd�dd�dd�d d�dd�d d �d d �d d �d d �d!d!�d"d"�d#d$ddd%dddddd&� 6 �Z,g d'�Z-e-D ]Z.eD ]Z/e.� d(e/� �Z0e,e. e,e0< q�q�d)D ]Z.eD ] Z/e.� d(e/� �Z1e1e,e1< q�q�e D ] Z2d*e2� �e,d*e2� �< q�d[d/d0�Z3d\d3d4�Z4d]d^d8d9�Z5G d:d;� d;�Z6G d<d=� d=e6�Z7d_d@dA�Z8d`dEdF�Z9dadGdH�Z:dadIdJ�Z;dbdKdL�Z<dcdOdP�Z=dddRdS�Z>dddTdU�Z?dddVdW�Z@dddXdY�ZAg dZ�ZBdS )e� )� annotationsN)� unique_deltas)� Timestamp�get_unit_from_dtype�periods_per_day�tz_convert_from_utc)�DAYS� MONTH_ALIASES� MONTH_NUMBERS�MONTHS�int_to_weekday)�build_field_sarray�month_position_check)� 7 BaseOffset� 8 DateOffset�Day� _get_offset� to_offset)�get_rule_month)�npt)�cache_readonly)�find_stack_level)�is_datetime64_dtype�is_period_dtype�is_timedelta64_dtype)�ABCIndex� ABCSeries)�unique�WEEKDAY�DZEOM�M�BM�BQS�Q�QS�BQ�BA�A�AS�BAS�MS�C�B�T�S�L�U�N�H�W) 9 r1 r2 r# r' r3 r �Y�BY�YS�BYS) r$ r% r" r6 r( r5 r& r7 r) �-)r' r# �W-� 10 offset_str�str�return� 11 str | Nonec C s t �| d�S )z4 12 Alias to closest period strings BQ->Q etc. 13 N)�_offset_to_period_map�get)r: � r@ ��C:\Users\Jacks.GUTTSPC\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\pandas\tseries\frequencies.py�get_period_aliasb � rB �namer c C s t jdtt� d� t| �S )z� 14 Return DateOffset object associated with rule name. 15 16 .. deprecated:: 1.0.0 17 18 Examples 19 -------- 20 get_offset('EOM') --> BMonthEnd(1) 21 zXget_offset is deprecated and will be removed in a future version, use to_offset instead.�� 22 stacklevel)�warnings�warn� FutureWarningr r )rD r@ r@ rA � 23 get_offseti s 24 �rJ TrH �boolc C s� ddl m}m}m}m} t| t�r+| j}t|�s)t |�s)|j 25 t ks)t d| j 26 � ���|} t | d�s1nt| j 27 �r:t d��t | j 28 �rIt| |d�}|�� S t| |�rft| |�sft| ||f�rct dt| �� ���| j} t| |�so|| �} t| |d�}|�� S )a} 29 Infer the most likely frequency given the input index. 30 31 Parameters 32 ---------- 33 index : DatetimeIndex or TimedeltaIndex 34 If passed a Series will use the values of the series (NOT THE INDEX). 35 warn : bool, default True 36 .. deprecated:: 1.5.0 37 38 Returns 39 ------- 40 str or None 41 None if no discernible frequency. 42 43 Raises 44 ------ 45 TypeError 46 If the index is not datetime-like. 47 ValueError 48 If there are fewer than three values. 49 50 Examples 51 -------- 52 >>> idx = pd.date_range(start='2020/12/01', end='2020/12/30', periods=30) 53 >>> pd.infer_freq(idx) 54 'D' 55 r )� DatetimeIndex� Float64Index�Index� 56 Int64Indexz>cannot infer freq from a non-convertible dtype on a Series of �dtypezJPeriodIndex given. Check the `freq` attribute instead of using infer_freq.)rH z4cannot infer freq from a non-convertible index type )�pandas.core.apirL rM rN rO � 57 isinstancer �_valuesr r rP �object� TypeError�hasattrr �_TimedeltaFrequencyInferer�get_freq�type�_FrequencyInferer)�indexrH rL rM rN rO �valuesZinfererr@ r@ rA � 58 infer_freq� sB 59 �� 60 �� 61 62 � 63 � 64 r] c @ s e Zd ZdZd5d6dd�Zed7d 65 d ��Zed7d d ��Zed8dd��Zed8dd��Z d9dd�Z 66 ed:dd��Z ed:dd��Z ed;dd ��Z ed<d d ��Zd9d d!�Zed7d"d#��Zed7d$d%��Zd9d&d'�Zd9d(d)�Zd9d*d+�Zd9d,d-�Zd9d.d/�Zd8d0d1�Zd9d2d3�Zd4S )=rZ z8 67 Not sure if I can avoid the state machine here 68 TrH rK r< �Nonec C s� || _ |j| _t|t�rt|jjj�| _ nt|jj�| _ t 69 |d�r.|j d ur.t | j|j �| _|dur;t jdtt� d� || _t|�dk rHtd��| j jpO| j j| _d S )N�tzTzSwarn is deprecated (and never implemented) and will be removed in a future version.rE � z(Need at least 3 dates to infer frequency)r[ �asi8�i8valuesrR r r �_data�_ndarrayrP �_resorV r_ r rG rH rI r �len� 70 ValueError�_is_monotonic_increasing�_is_monotonic_decreasing� is_monotonic)�selfr[ rH r@ r@ rA �__init__� s* 71 � 72 73 � �z_FrequencyInferer.__init__�npt.NDArray[np.int64]c C s 74 t | j�S �N)r rb �rk r@ r@ rA �deltas� s 75 z_FrequencyInferer.deltasc C s t | jj�S rn )r r[ ra ro r@ r@ rA � deltas_asi8� rC z _FrequencyInferer.deltas_asi8c C � t | j�dkS �N� )rf rp ro r@ r@ rA � is_unique � z_FrequencyInferer.is_uniquec C rr rs )rf rq ro r@ r@ rA �is_unique_asi8 rv z _FrequencyInferer.is_unique_asi8r= c C s | j r| jjs dS | jd }t| j�}|r t||�r | �� S | jddgddgg d�fv r.dS | j s3dS | j 76 d }|d }|d }|d }t||�rPt d 77 || �S t||�r\t d || �S t||�rht d || �S t||d �rxt d||d �S t||d �r�t d||d �S t d|�S )z� 78 Find the appropriate frequency string to describe the inferred 79 frequency of self.i8values 80 81 Returns 82 ------- 83 str or None 84 Nr rt � �A )rt rx ry ZBH� �< r2 r- r. i� r/ i@B r0 r1 ) rj r[ � 85 _is_uniquerp r re � _is_multiple�_infer_daily_rule� hour_deltasrw rq �_maybe_add_count)rk �delta�ppd�pph�ppm�ppsr@ r@ rA rX 86 s2 87 88 89 90 91 92 93 z_FrequencyInferer.get_freq� list[int]c s t | j�� � fdd�| jD �S )Nc � g | ]}|� �qS r@ r@ ��.0�x�r� r@ rA � 94 <listcomp>? � z0_FrequencyInferer.day_deltas.<locals>.<listcomp>�r re rp ro r@ r� rA � 95 day_deltas< s 96 z _FrequencyInferer.day_deltasc s" t | j�d � � fdd�| jD �S )Nrz c r� r@ r@ r� �r� r@ rA r� D r� z1_FrequencyInferer.hour_deltas.<locals>.<listcomp>r� ro r@ r� rA r A s z _FrequencyInferer.hour_deltas� 97 np.ndarrayc C s t | j| jd�S )N)�reso)r rb re ro r@ r@ rA �fieldsF s z_FrequencyInferer.fieldsr c C s t | jd �S �Nr )r rb ro r@ r@ rA � rep_stampJ rv z_FrequencyInferer.rep_stampc C s t | j| jj�S rn )r r� r[ � dayofweekro r@ r@ rA r N s z&_FrequencyInferer.month_position_checkc C s& | j d d | j d }t|�d��S )Nr4 � r �i8)r� r �astype)rk Znmonthsr@ r@ rA �mdiffsQ s z_FrequencyInferer.mdiffsc C s t | jd �d��S )Nr4 r� )r r� r� ro r@ r@ rA �ydiffsV s z_FrequencyInferer.ydiffsc 98 C s� | � � }|r | jd }t| jj }|� d|� �}t||�S | �� }|rF| jd d }dddd�}t|| jjd }|� d|� �}t||�S | �� }|rTt|| jd �S | j r[| � 99 � S | � � radS | � � } | ri| S d S ) Nr r8 r` r� � � 100 )r � rt r, ) �_get_annual_ruler� r r� �monthr� �_get_quarterly_ruler� �_get_monthly_ruleru �_get_daily_rule�_is_business_daily� _get_wom_rule) 101 rk Z annual_rule�nyearsr� �aliasZquarterly_ruleZ nquarters�mod_dictZ monthly_ruleZwom_ruler@ r@ rA r~ Z s0 102 103 104 z#_FrequencyInferer._infer_daily_rulec C sT t | j�}| jd | }|d dkr%t| j�� }d|� �}t||d �S td|�S )Nr � r9 r )r re rp r r� �weekdayr� )rk r� �days�wdr� r@ r@ rA r� z s 105 106 107 z!_FrequencyInferer._get_daily_rulec C sT t | j�dkr d S t t| jd ��dkrd S | �� }|d u r d S ddddd��|�S )Nrt r r( r) r' r& ��cs�bs�ce�be)rf r� r r� r r? �rk Z pos_checkr@ r@ rA r� � s z"_FrequencyInferer._get_annual_rulec C sP t | j�dkr d S | jd d dksd S | �� }|d u r d S ddddd��|�S ) Nrt r r` r$ r" r# r% r� �rf r� r r? r� r@ r@ rA r� � s z%_FrequencyInferer._get_quarterly_rulec C s: t | j�dkr d S | �� }|d u rd S ddddd��|�S )Nrt r* ZBMSr r! r� r� r� r@ r@ rA r� � s z#_FrequencyInferer._get_monthly_rulec C s� | j ddgkr dS | jd �� }t�| jj�}t| j�}t�||�}t� |t� 108 |� d�}t t� |dk|dk@ |dk|dk@ |dk@ B ��S )Nrt r` Fr r� � ) r� r[ r� �np�diffra r re � floor_divide�mod�cumsumrK �all)rk � first_weekday�shiftsr� �weekdaysr@ r@ rA r� � s 109 ���z$_FrequencyInferer._is_business_dailyc C s~ t | jj�}t|�dkrd S t | jjd d �}||dk }t|�dks*t|�dkr,d S |d d }t|d }d|� |� �S )Nrt r� r� r zWOM-)r r[ r� rf �dayr )rk r� Zweek_of_months�weekr� r@ r@ rA r� � s z _FrequencyInferer._get_wom_ruleN�T)rH rK r< r^ )r< rm �r< rK )r< r= )r< r� )r< r� )r< r )�__name__� 110 __module__� __qualname__�__doc__rl r rp rq ru rw rX r� r r� r� r r� r� r~ r� r� r� r� r� r� r@ r@ r@ rA rZ � s@ & 111 2 112 113 114 115 116 117 118 119 rZ c @ s e Zd Zdd� ZdS )rW c C s | j r| �� S d S rn )ru r� ro r@ r@ rA r~ � s �z,_TimedeltaFrequencyInferer._infer_daily_ruleN)r� r� r� r~ r@ r@ r@ rA rW � s rW �mult�intc C s | | dkS r� r@ )�usr� r@ r@ rA r} � s r} �base�count�floatc C s0 |dkr|t |�ks J �t |�}|� | � �S | S rs )r� )r� r� r@ r@ rA r� � s 120 r� c C s& |du s| du r 121 dS t | �} t |�}t|�r't| �r#tt| �t|��S | dv S t|�r/| dv S t|�r7| dv S t|�rI| |ddddd d 122 d d d h 123 v S |dkrQ| dv S |dkrY| dv S |dkra| dv S |dkri| dv S |d krq| dv S |d 124 kry| dv S |d kr�| dv S |d kr�| dv S |d kr�| dv S dS )a 125 Returns True if downsampling is possible between source and target 126 frequencies 127 128 Parameters 129 ---------- 130 source : str or DateOffset 131 Frequency converting from 132 target : str or DateOffset 133 Frequency converting to 134 135 Returns 136 ------- 137 bool 138 NF� 139 r1 r2 r r r0 r/ r- r, r+ r. � r1 r2 r r0 r/ r- r, r+ r. r r+ r, r2 r- r. r/ r0 r1 > r1 r2 r0 r/ r- r, r. > r1 r2 r0 r/ r- r+ r. > r1 r2 r r0 r/ r- r. � r1 r2 r0 r/ r- r. � r1 r0 r/ r- r. � r1 r. r0 r/ � r1 r0 r/ � r1 r0 � r1 )�_maybe_coerce_freq� 140 _is_annual� _is_quarterly�_quarter_months_conformr � _is_monthly� 141 _is_weekly)�source�targetr@ r@ rA � is_subperiod� sF � r� c C sF |du s| du r 142 dS t | �} t |�}t| �r7t|�r"t| �t|�kS t|�r3t| �}t|�}t||�S |dv S t| �r?|dv S t| �rG|dv S t| �rY|| ddddd d 143 d d d h 144 v S | dkra|dv S | dkri|dv S | dkrq|dv S | dkry|dv S | d kr�|dv S | d 145 kr�|dv S | d kr�|dv S | d kr�|dv S | d kr�|dv S dS )a 146 Returns True if upsampling is possible between source and target 147 frequencies 148 149 Parameters 150 ---------- 151 source : str or DateOffset 152 Frequency converting from 153 target : str or DateOffset 154 Frequency converting to 155 156 Returns 157 ------- 158 bool 159 NFr� r� r r+ r, r2 r- r. r/ r0 r1 r� r� r� r� r� r� )r� r� r r� r� r� r� )r� r� ZsmonthZtmonthr@ r@ rA �is_superperiod% sJ 160 r� c C s$ | dusJ �t | t�r| j} | �� S )z�we might need to coerce a code to a rule_code 161 and uppercase it 162 163 Parameters 164 ---------- 165 source : str or DateOffset 166 Frequency converting from 167 168 Returns 169 ------- 170 str 171 N)rR r � rule_code�upper)�coder@ r@ rA r� _ s 172 r� r� r� c C s t | }t | }|d |d kS )Nr` )r 173 )r� r� Zsnum�tnumr@ r@ rA r� r s r� �rulec C � | � � } | dkp | �d�S )Nr' zA-�r� � 174 startswith�r� r@ r@ rA r� x � r� c C s$ | � � } | dkp| �d�p| �d�S )Nr# zQ-r% r� r� r@ r@ rA r� } s r� c C s | � � } | dkp | dkS )Nr r! )r� r� r@ r@ rA r� � s r� c C r� )Nr3 r9 r� r� r@ r@ rA r� � r� r� )r rJ rB r] r� r� r )r: r; r< r= )rD r; r< r r� )rH rK r< r= )r� r� r< rK )r� r; r� r� r< r; r� )r< r; )r� r; r� r; r< rK )r� r; r< rK )C� 175 __future__r rG �numpyr� �pandas._libs.algosr �pandas._libs.tslibsr r r r Z pandas._libs.tslibs.ccalendarr r r 176 r r �pandas._libs.tslibs.fieldsr r �pandas._libs.tslibs.offsetsr r r r r �pandas._libs.tslibs.parsingr �pandas._typingr �pandas.util._decoratorsr �pandas.util._exceptionsr �pandas.core.dtypes.commonr r r �pandas.core.dtypes.genericr r �pandas.core.algorithmsr r> � _need_suffix�_prefix�_m�key�_alias�_drB rJ r] rZ rW r} r� r� r� r� r� r� r� r� r� �__all__r@ r@ r@ rA �<module> s� �������� � 177 � � � ������ � 178 � 179 180 M 181 182 183 184 8 185 : 186 187 188 189 190