從python/pandas中的日期/時間格式計算年齡

Question

尋找一種方法來計算python中以下日期/時間格式的年齡。

例如：1956-07-01T00：00：00Z

我已經寫了代碼通過提取字符串的四個字符，將其轉換爲int和2017減去它這樣做，但一直在尋找看看是否有一個有效的方法來做到這一點。

Answer 1

這是你想要的嗎？

(pd.to_datetime('today').year-pd.to_datetime('1956-07-01').year) 

Out[83]: 61 

Answer 2

我由365.25

(pd.to_datetime('today') - pd.to_datetime('1956-07-01')).days/365.25 

61.24845995893224 

Answer 3

劃分經由timedelta對象的天數如果有如下的不規則年（例如1601），pd.to_datetime將是一個誤差。

import pandas as pd 

(pd.to_datetime('today').year-pd.to_datetime('1601-07-01').year) 

# Traceback (most recent call last): 
# File "/home/kuroyanagi/.pyenv/versions/anaconda3-4.4.0/lib/python3.6/site-packages/pandas/core/tools/datetimes.py", line 444, in _convert_listlike 
#  values, tz = tslib.datetime_to_datetime64(arg) 
# File "pandas/_libs/tslib.pyx", line 1810, in pandas._libs.tslib.datetime_to_datetime64 (pandas/_libs/tslib.c:33275) 
# TypeError: Unrecognized value type: <class 'str'> 
# During handling of the above exception, another exception occurred: 
# Traceback (most recent call last): 
# File "/home/kuroyanagi/.pyenv/versions/anaconda3-4.4.0/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 2881, in run_code 
#  exec(code_obj, self.user_global_ns, self.user_ns) 
# File "<ipython-input-45-829e219d9060>", line 1, in <module> 
#  (pd.to_datetime('today').year-pd.to_datetime('1601-07-01').year) 
# File "/home/kuroyanagi/.pyenv/versions/anaconda3-4.4.0/lib/python3.6/site-packages/pandas/core/tools/datetimes.py", line 518, in to_datetime 
#  result = _convert_listlike(np.array([arg]), box, format)[0] 
# File "/home/kuroyanagi/.pyenv/versions/anaconda3-4.4.0/lib/python3.6/site-packages/pandas/core/tools/datetimes.py", line 447, in _convert_listlike 
#  raise e 
# File "/home/kuroyanagi/.pyenv/versions/anaconda3-4.4.0/lib/python3.6/site-packages/pandas/core/tools/datetimes.py", line 435, in _convert_listlike 
#  require_iso8601=require_iso8601 
# File "pandas/_libs/tslib.pyx", line 2355, in pandas._libs.tslib.array_to_datetime (pandas/_libs/tslib.c:46617) 
# File "pandas/_libs/tslib.pyx", line 2538, in pandas._libs.tslib.array_to_datetime (pandas/_libs/tslib.c:45511) 
# File "pandas/_libs/tslib.pyx", line 2506, in pandas._libs.tslib.array_to_datetime (pandas/_libs/tslib.c:44978) 
# File "pandas/_libs/tslib.pyx", line 2500, in pandas._libs.tslib.array_to_datetime (pandas/_libs/tslib.c:44859) 
# File "pandas/_libs/tslib.pyx", line 1517, in pandas._libs.tslib.convert_to_tsobject (pandas/_libs/tslib.c:28598) 
# File "pandas/_libs/tslib.pyx", line 1774, in pandas._libs.tslib._check_dts_bounds (pandas/_libs/tslib.c:32752) 
# pandas._libs.tslib.OutOfBoundsDatetime: Out of bounds nanosecond timestamp: 1601-07-01 00:00:00 

對於包含非正常年份的數據，您可以計算如下。

import numpy as np 
import pandas as pd 

date = pd.Series(['1601-07-01', '1956-07-01']) 

def elasped_years(date): 
    reference_year = pd.to_datetime('today').year 
    reference_month = pd.to_datetime('today').month 
    year = date.str.slice(0, 4).astype(np.float) 
    month = date.str.slice(5, 7).astype(np.float) 
    duration = np.floor((12 * (reference_year - year) + (reference_month - month))/12) 
    return(duration) 

elasped_years(date) 
# Out[46]: 
# 0 416.0 
# 1  61.0 
# dtype: float64