{"id":2708,"date":"2021-03-04T13:21:43","date_gmt":"2021-03-04T04:21:43","guid":{"rendered":"https:\/\/qol-kk.com\/wp2\/?p=2708"},"modified":"2021-03-04T13:21:43","modified_gmt":"2021-03-04T04:21:43","slug":"post-2708","status":"publish","type":"post","link":"https:\/\/qol-kk.com\/wp2\/blog\/2021\/03\/04\/post-2708\/","title":{"rendered":"Python\uff1aPandas\u306e\u65e5\u4ed8\u51e6\u7406\u306f\u30af\u30bb\u304c\u51c4\u3044\u306e\u3067\u8ff7\u308f\u306a\u3044\u70ba\u306e\u5099\u5fd8\u9332"},"content":{"rendered":"

Python\uff1aPandas\u306e\u65e5\u4ed8\u51e6\u7406\u306f\u30af\u30bb\u304c\u51c4\u3044\u306e\u3067\u8ff7\u308f\u306a\u3044\u70ba\u306e\u5099\u5fd8\u9332<\/h2>\n

\u6700\u8fd1\u8abf\u3079\u308b\u56de\u6570\u304c\u591a\u3044Pandas\u306e\u65e5\u4ed8\u51e6\u7406\u3002
\n\u6bce\u56de\u9055\u3046\u4e8b\u3067\u60a9\u3093\u3067\u3044\u308b\u306e\u3067\u3059\u304c\u300c\u3053\u3093\u306a\u60a9\u307f\u3092\u751f\u3080\u4ed5\u7d44\u307f\u3063\u3066\u3042\u308b\u610f\u5473\u51c4\u3044\u300d\u3068\u601d\u3063\u3066\u3044\u307e\u3059\u3002
\n\u3068\u8a00\u3046\u4e8b\u3067\u3001Pandas\u3067\u306e\u65e5\u4ed8\u51e6\u7406\u306b\u3064\u3044\u3066\u8ff7\u308f\u306a\u3044\u70ba\u306e\u57fa\u672c\u4e8b\u9805\u3092\u307e\u3068\u3081\u3066\u304a\u304d\u307e\u3059\u3002<\/p>\n

\u307e\u305a\u982d\u306b\u5165\u308c\u3066\u304a\u304b\u306a\u3044\u3068\u3044\u3051\u306a\u3044\u306e\u306f\u30b3\u30ec\u3067\u3059\u3002<\/p>\n

DataFrame\u306b\u683c\u7d0d\u3059\u308b\u3068\u30ab\u30e9\u30e0\u306e\u5024\u306fSeries\u306b\u306a\u308a\u6587\u5b57\u5217\u3068\u3057\u3066\u683c\u7d0d\u3055\u308c\u308b<\/div>\n

\u203bdatetime64[ns]\u578b\u306eDataFrame\u3067\u65e5\u4ed8\u3092Index\u3068\u3057\u305f\u5834\u5408DatetimeIndex\u3068\u306a\u308a\u69d8\u3005\u306a\u6a5f\u80fd\u3092\u4f7f\u3048\u308b\u3088\u3046\u306b\u306a\u308a\u307e\u3059\u304c\u4eca\u56de\u306f\u89e6\u308c\u307e\u305b\u3093\u3002<\/p>\n

DataFrame\u306b\u5909\u63db\u3059\u308b\u3068\u6587\u5b57\u5217\u306b\u306a\u308b\u304cSeries\u306f\u666e\u901a\u306e\u6587\u5b57\u5217\u3068\u306f\u9055\u3046<\/h3>\n

\u6587\u5b57\u5217\u306e\u65e5\u4ed8\u3092datetime\u578b\u306b\u5909\u63db\u3059\u308b\u30b3\u30fc\u30c9<\/p>\n

import datetime as dt\r\nstr_dateA = '2021-03-04'\r\n\r\n# datetime\u578b\u3078\u5909\u63db\r\ndt_dateA = dt.datetime.strptime(str_dateA, '%Y-%m-%d')\r\n# \u66f4\u306bdatetime.date\u3078\u5909\u63db\r\ndtdate_dateA = dt.date(dt_dateA.year, dt_dateA.month, dt_dateA.day)<\/pre>\n
\u3053\u308c\u3092DataFrame\u306b\u5bfe\u3057\u3066\u5b9f\u884c\u3059\u308b\u3068\u30a8\u30e9\u30fc\u304c\u767a\u751f\u3057\u307e\u3059\u3002<\/p>\n
cannot convert the series to <class 'int'>
\n\u8a33\uff1a\u7cfb\u5217\u3092 <class 'int'> \u306b\u5909\u63db\u3059\u308b\u3053\u3068\u306f\u3067\u304d\u307e\u305b\u3093\u3002 \u203b\u7cfb\u5217\uff1dSeries<\/span><\/div>\n
\u3068\u8a00\u3046\u4e8b\u3067Pandas\u306b\u683c\u7d0d\u3057\u305f\u6642\u70b9\u3067datetime\u95a2\u6570\u306f\u5229\u7528\u3067\u304d\u307e\u305b\u3093\u3002
\n\u540c\u3058\u6587\u5b57\u5217\u3067\u306f\u3042\u308a\u307e\u3059\u304cSeries\u3068\u3044\u3046\u30bf\u30b0\u4ed8\u304d\u306e\u6587\u5b57\u5217\u3067\u3042\u308a\u30d4\u30e5\u30a2\u306a\u6587\u5b57\u5217\u3068\u306f\u9055\u3044\u307e\u3059\u3002
\n\u3053\u308c\u304c\u5730\u5473\u306b\u75db\u3044...\u3002<\/p>\n
Series\u306b\u3042\u308b\u65e5\u4ed8\u306fto_datetime\u95a2\u6570\u3067Datetime\u3082\u3069\u304d\u306b\u5909\u63db\u3059\u308b<\/h3>\n
to_datetime\u95a2\u6570\u306fDataFrame\u306b\u5165\u3063\u3066\u3044\u308b\u65e5\u4ed8\u30c7\u30fc\u30bf\u3092DatetimeLike\u306b\u6271\u3048\u308b\u3088\u3046\u306b\u5909\u63db\u3057\u3066\u304f\u308c\u307e\u3059\u3002<\/p>\n
import datetime as dt \r\nimport pandas as pd\r\n\r\n# DataFrame\r\n# \u4e0b\u306f\u30c7\u30fc\u30bf\u578b=Date\u3067SQL\u306b\u683c\u7d0d\u3055\u308c\u305f\u5024\u3092 df_data = pd.DataFrame(data)\u3067DataFrame\u5316\r\nprint (df_date)\r\n   start       end\r\n0  2020-12-20  2021-01-03\r\n1  2021-01-22  2021-03-01\r\n2  2021-02-05  2021-03-04\r\n3  2021-03-01  2021-03-01\r\n\r\n# Series \u3092DatetimeLike\u306a\u5f62\u306b\u5909\u63db\r\nldt_date_start =  pd.todatetime(df_date['start'])\r\n\r\nprint(ldt_date_start.dt.day)\r\n # 20 22 05 01\r\nprint(ldt_date_start.dt.month)\r\n # 12 01 02 03<\/pre>\n
\u305f\u3060\u3057\u3001\u3042\u304f\u307e\u3067\u3082DatatimeLike\u3067\u3042\u3063\u3066\u5b8c\u5168\u4e00\u81f4\u3067\u540c\u3058\u51e6\u7406\u306f\u3067\u304d\u307e\u305b\u3093\u3002
\n\u3010\u3082\u3069\u304d\u3011\u3067\u3042\u308b\u4e8b\u306e\u7406\u89e3\u304c\u91cd\u8981\u3067\u3059\u3002<\/p>\n
Print\u3067\u65e5\u4ed8\u3084\u6708\u3092\u53d6\u308a\u51fa\u305b\u308b\u306e\u3060\u304b\u3089datetime.date\u306b\u3059\u308b\u3053\u3068\u3082\u3067\u304d\u308b\u3093\u3058\u3083\u306a\u3044\u304b\u3068\u601d\u3044\u30c6\u30b9\u30c8\u3057\u3066\u307f\u307e\u3057\u305f\u3002<\/p>\n
# \u5f37\u5f15\u306bdatetime.date\u306b\u7f6e\u63db\u3048\u3066\u307f\u308b\r\ndt_dateA = dt.date(ldt_date_start.dt.year,ldt_date_start.dt.month,ldt_date_start.dt.day)<\/pre>\n
descriptor 'date' for 'datetime.datetime' objects doesn't apply to a 'Series' object
\n\u8a33\uff1adatetime.datetime'\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306e\u30c7\u30a3\u30b9\u30af\u30ea\u30d7\u30bf'date'\u306f'Series'\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b\u306f\u9069\u7528\u3055\u308c\u307e\u305b\u3093\u3002<\/span><\/div>\n
\u3084\u306f\u308aSeries\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3067\u3042\u308b\u70b9\u304c\u30cd\u30c3\u30af\u3068\u306a\u308adate\u578b\u3078\u306e\u5909\u63db\u306f\u5931\u6557\u3057\u307e\u3057\u305f\u3002
\n\u4eca\u56de\u4f7f\u3044\u305f\u304b\u3063\u305f\u5dee\u5206\u306e\u6708\u6570\u3092\u8a08\u7b97\u3059\u308b\u95a2\u6570\u3010monthmod\u3011\u306fdatetime\u578b\u3067\u3042\u308b\u5fc5\u8981\u304c\u3042\u308b\u305f\u3081\u6483\u6c88\u3002
\n\u3053\u306e\u4e8b\u4f8b\u306e\u3088\u3046\u306b\u3001Datatime\u3092\u4f7f\u3063\u3066\u30b4\u30cb\u30e5\u30b4\u30cb\u30e7\u3059\u308b\u95a2\u6570\u7cfb\u306f\u5927\u304d\u306a\u5f71\u97ff\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n
Series\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306fto_datetime\u306a\u3057\u3067\u3082\u300e\u306a\u305c\u304b\u300f\u65e5\u4ed8\u306e\u5dee\u5206\u8a08\u7b97\u306f\u884c\u3046<\/h3>\n
\u3053\u306e\u52d5\u4f5c\u304c\u79c1\u3092\u8aa4\u89e3\u3055\u305b\u3066\u9577\u8003\u306e\u304d\u3063\u304b\u3051\u306b\u306a\u3063\u3066\u307e\u3057\u305f\u3002<\/p>\n
DataFrame\u306b\u683c\u7d0d\u3059\u308b\u3068\u30ab\u30e9\u30e0\u306e\u5024\u306fSeries\u306b\u306a\u308a\u6587\u5b57\u5217\u3068\u3057\u3066\u683c\u7d0d\u3055\u308c\u308b<\/div>\n
\u539f\u5247\u304b\u3089\u8003\u3048\u308c\u3070\u6587\u5b57\u5217\u306a\u306e\u3067\u6e1b\u7b97\u51e6\u7406\u306a\u3093\u3066\u51fa\u6765\u306a\u3044\u30cf\u30ba\u3002
\n\u3067\u3082\u3067\u304d\u308b\u3093\u3067\u3059\u3088\u306d\u3002\u306a\u3093\u3067\u3067\u3057\u3087\u3046\u3002<\/p>\n
import datetime as dt \r\nimport pandas as pd\r\n\r\n# DataFrame\r\n# \u4e0b\u306f\u30c7\u30fc\u30bf\u578b=Date\u3067SQL\u306b\u683c\u7d0d\u3055\u308c\u305f\u5024\u3092 df_data = pd.DataFrame(data)\u3067DataFrame\u5316\r\nprint (df_date)\r\n   start       end\r\n0  2020-12-20  2021-01-03\r\n1  2021-01-22  2021-03-01\r\n2  2021-02-05  2021-03-04\r\n3  2021-03-01  2021-03-01\r\n\r\n# start\u3068end\u306e\u5dee\u5206\uff08\u671f\u9593\uff09\u3092\u6c42\u3081\u308b\r\ndiff_date =  df_date['end'] - df_date['start']\r\n\r\nprint(diff_date)\r\n # 14 days 00:00:00 38 days 00:00:00 27 days 00:00:00 0 days 00:00:00\r\n\r\n# \u65e5\u4ed8\u3060\u3051\u53d6\u308a\u51fa\u3059\u3053\u3068\u3082\u3067\u304d\u308b\r\ndiff_date = (df_date['end'] - df_date['start']).dt.days\r\n\r\nprint(diff_date)\r\n # 14 38 27 0<\/pre>\n
\u300c\u8a08\u7b97\u3067\u304d\u308b\u306a\u3089dt\u30aa\u30d7\u30b7\u30e7\u30f3\u3067\u3010 .dt.year \u3011\u3068\u304b\u500b\u5225\u53d6\u5f97\u3067\u304d\u308b\u3093\u3058\u3083\u306d\uff1f\u300d\u3068\u601d\u3044\u5b9f\u9a13\u3002<\/p>\n
# \u683c\u7d0d\u3057\u305f\u59ff\u305d\u306e\u307e\u307e\u3067\u5e74\u3060\u3051\u53d6\u308a\u51fa\u3057\u3066\u307f\u308b\r\npu_year = df_date['start'].dt.year\r\n<\/pre>\n
Can only use .dt accessor with datetimelike values
\n\u8a33\uff1adatetimelike \u5024\u3092\u6301\u3064 .dt \u30a2\u30af\u30bb\u30b5\u306e\u307f\u3092\u4f7f\u7528\u3067\u304d\u307e\u3059\u3002<\/span><\/div>\n
\u3084\u3063\u3071\u308a\u3067\u304d\u306a\u3044\u3002\u307e\u3041\u3053\u308c\u304c\u6a19\u6e96\u3067\u3059\u3088\u306d\u3002
\n\u3067\u300c\u8a08\u7b97\u7d50\u679c\u3092DataFrame\u306b\u683c\u7d0d\u3057\u305f\u5f8c\u306btd.days\u3067\u53d6\u5f97\u3059\u308b\u3068\u5931\u6557\u3059\u308b\u3060\u308d\u3046\u300d\u3068\u601d\u3044\u304d\u3084\u3001\u3053\u308c\u306f\u901a\u308a\u307e\u3059\u3002<\/p>\n
df_date['diff'] = df_date['end'] - df_date['start']\r\ndiff_list = df_date['diff'].dt.days\r\n\r\nprint(diff_list)\r\n # 14 38 27 0<\/pre>\n
for\u30eb\u30fc\u30d7\u3059\u308b\u3068to_datetime\u306a\u3057\u3067datetime\u3068\u3057\u3066\u6271\u3046\u3053\u3068\u304c\u3067\u304d\u308b<\/h3>\n
\u300c\u6298\u89d2DataFrame\u306b\u3057\u305f\u306e\u3092For\u30eb\u30fc\u30d7\u3067\u30ea\u30b9\u30c8\u306b\u623b\u3059\u306e?\u300d\u3068\u3044\u3046\u3054\u610f\u898b\u304c\u3042\u308b\u306e\u306f\u91cd\u3005\u627f\u77e5\u3057\u3066\u307e\u3059\u3002
\n\u306a\u306e\u3067\u3053\u308c\u3082\u5b9f\u9a13\u3068\u8a00\u3046\u4e8b\u3067\u3002
\n\u5148\u306b\u632f\u308c\u305f\u3088\u3046\u306b\u3001monthmod\u3068\u3044\u3046datetime\u3092\u5229\u7528\u3057\u305f\u7d4c\u904e\u6708\u6570\u8a08\u7b97\u95a2\u6570\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n
pip install MonthDelta
\nUse\u306f from monthdelta import monthmod<\/span><\/div>\n
\u3053\u308c\u3092For\u30eb\u30fc\u30d7\u306a\u3057\u3067\u4f7f\u3063\u3066\u307f\u307e\u3059\u3002<\/p>\n
test = monthmod(df['operation__startdate'],df['operation__enddate'])<\/pre>\n
start and end must be dates
\n\u8a33\uff1a\u958b\u59cb\u3068\u7d42\u4e86\u306f\u65e5\u4ed8\u3067\u306a\u3051\u308c\u3070\u306a\u308a\u307e\u305b\u3093<\/span><\/div>\n
\u3053\u3093\u306a\u30a8\u30e9\u30fc\u304c\u51fa\u3066\u304d\u307e\u3059\u3002\u3053\u308c\u306fto_datetime\u3092\u5229\u7528\u3057\u3066\u3082\u540c\u3058\u7d50\u679c\u3067\u3059\u3002
\n\u3067\u306f\u3001for\u30eb\u30fc\u30d7\u3092\u4f7f\u3063\u3066\u8d70\u3089\u305b\u3066\u307f\u307e\u3059\u3002<\/p>\n
test = []\r\nfor index, item in df.iterrows():\r\n    test.append(monthmod(item['start'],item['end']))\r\n\r\nprint(test)\r\n # [(monthdelta(0), datetime.timedelta(days=14)), \r\n    (monthdelta(1), datetime.timedelta(days=7)),\r\n    (monthdelta(0), datetime.timedelta(days=27)),\r\n    (monthdelta(0), datetime.timedelta(days=0))]<\/pre>\n
\u901a\u308a\u307e\u3057\u305f\u306d\u3002
\n\u305d\u308c\u3082\u6587\u5b57\u5217\u21d2datetime\u5909\u63db\u3092\u3057\u306a\u3044\u72b6\u614b\u3067\u901a\u3063\u3066\u307e\u3059\u3002
\n\u3046\uff5e\u3093\u3001\u6587\u5b57\u5217\u3068\u3057\u3066\u683c\u7d0d\u3055\u308c\u308b\u3068\u304b\u8a00\u3063\u3068\u3044\u3066\u4e0d\u601d\u8b70\u306a\u52d5\u304d\u3067\u3059\u3002<\/p>\n
Pandas\u306e\u65e5\u4ed8\u64cd\u4f5c\u3067\u3088\u304f\u4f7f\u3046\u30b3\u30de\u30f3\u30c9<\/h3>\n
\u4eca\u56de\u306fDataFrame\u5185\u306e\u65e5\u4ed8\u30c7\u30fc\u30bf\u306e\u57fa\u672c\u7684\u306a\u52d5\u304d\u3068\u3057\u3066\u307e\u3068\u3081\u3066\u307f\u307e\u3057\u305f\u3002<\/p>\n
\u6700\u5f8c\u306b\u30b3\u30de\u30f3\u30c9\u3068\u3057\u3066\u3088\u304f\u4f7f\u3046\u3082\u306e\u3092\u307e\u3068\u3081\u3066\u307f\u307e\u3059\u3002<\/p>\n
\n
    \n
  1. Series\u306e\u65e5\u4ed8\u5909\uff5c pd.to_datetime(df['date'])\u3000\u203bimport pandas as pd<\/li>\n
  2. \u300c\u5e74\u300d\u3060\u3051\u53d6\u5f97\uff5c pd.to_datetime(df['date']).dt.year\u3000\u203b dt.month\u21d2\u300c\u6708\u300d\u53d6\u5f97 \/ dt.day\u21d2\u300c\u65e5\u300d\u53d6\u5f97<\/li>\n
  3. \u66dc\u65e5\u306e\u53d6\u5f97\uff5c pd.to_datetime(df['date']).dt.dayofweek\u3000\u203b \u6708\u66dc\u30920\u3068\u3057\u30660\uff5e6\u307e\u3067\u306e\u6570\u5b57\u3067\u66dc\u65e5\u3092\u8fd4\u3059 6=\u65e5\u66dc\u65e5<\/li>\n
  4. \u65e5\u6570\u306e\u52a0\u6e1b\u7b97_1\uff5c pd.tseries.offsets.Day(31)\u3000\u203b 20\u65e5\u524d\u306fpd.tseries.offsets.Day(-20)<\/li>\n
  5. \u65e5\u6570\u306e\u52a0\u6e1b\u7b97_2\uff5c dt + relativedelta(days=3)\u3000\u203b dt=\u5143\u306e\u65e5\u4ed8 \/ use \uff1afrom dateutil.relativedelta import relativedelta<\/li>\n
  6. \u9031\u6570\u3067\u52a0\u6e1b\u7b97\uff5c pd.tseries.offsets.Week(weekday=2)<\/li>\n
  7. \u65e5\u4ed8\u306e\u7f6e\u304d\u63db\u3048\uff5c dt + relativedelta(day=3)\u3000\u203b days=3\u3068\u3010s\u3011\u3092\u4ed8\u3051\u308b\u30683\u65e5\u5f8c\u3092\u8a08\u7b97\u3059\u308b\u306e\u3067\u8981\u6ce8\u610f<\/li>\n
  8. 2\u3064\u306e\u9593\u306e\u671f\u9593\uff5c (dt_A - dt_B).dt.days\u3000\u203b dt.days\u3092\u4ed8\u3051\u306a\u3044\u6642\u300120 days 00:00:00 \u306e\u3088\u3046\u306a\u5f62\u304c\u8fd4\u3063\u3066\u304f\u308b<\/li>\n
  9. for\u30eb\u30fc\u30d7\u3067\u5024\u3092\u53d6\u308b\uff5c for index, item in df.iterrows():\u3000\u203bindex\u4e0d\u8981\u306e\u6642\u306f\u5909\u65701\u3064\u3060\u3051\u3067OK<\/li>\n<\/ol>\n<\/div>\n
    dt\u30aa\u30d7\u30b7\u30e7\u30f3\u306e\u7d30\u304b\u3044\u60c5\u5831\u306f\u3053\u3061\u3089<\/a>\u306b\u307e\u3068\u307e\u3063\u3066\u307e\u3057\u305f\u3002<\/p>\n
    \u307e\u3068\u3081<\/h3>\n
    \u300cA\u3060\u3068\u51fa\u6765\u3066B\u3060\u3068\u51fa\u6765\u306a\u3044\u300d\u3068\u3044\u3046\u306e\u304c\u3042\u308b\u3068\u6163\u308c\u3066\u899a\u3048\u308b\u3057\u304b\u306a\u3044\u3002
    \n\u51e6\u7406\u3092\u66f8\u304f\u6570\u304c\u591a\u3044\u306e\u3067\u3001\u307e\u3041\u5acc\u3067\u3082\u899a\u3048\u3066\u3044\u304f\u3053\u3068\u3067\u3057\u3087\u3046\u3002<\/p>\n
    \u6700\u521d\u7c21\u5358\u306b\u65e5\u4ed8\u64cd\u4f5c\u304c\u3067\u304d\u305f\u306e\u306f\u300eDatetimeIndex\u306b\u3057\u3066\u305f\u304b\u3089\u300f\u3060\u3063\u305f\u3088\u3046\u3067\u3059\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"
    Python\uff1aPandas\u306e\u65e5\u4ed8\u51e6\u7406\u306f\u30af\u30bb\u304c\u51c4\u3044\u306e\u3067\u8ff7\u308f\u306a\u3044\u70ba\u306e\u5099\u5fd8\u9332 \u6700\u8fd1\u8abf\u3079\u308b\u56de\u6570\u304c\u591a\u3044Pandas\u306e\u65e5\u4ed8\u51e6\u7406\u3002 \u6bce\u56de\u9055\u3046\u4e8b\u3067\u60a9\u3093\u3067\u3044\u308b\u306e\u3067\u3059\u304c\u300c\u3053\u3093\u306a\u60a9\u307f\u3092\u751f\u3080\u4ed5\u7d44\u307f\u3063\u3066\u3042\u308b\u610f\u5473\u51c4\u3044\u300d\u3068\u601d\u3063\u3066\u3044\u307e\u3059\u3002 \u3068\u8a00\u3046\u4e8b\u3067\u3001 […]<\/p>\n","protected":false},"author":1,"featured_media":2173,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"sns_share_botton_hide":"","vkExUnit_sns_title":"","_vk_print_noindex":"","sitemap_hide":"","_veu_custom_css":"","veu_display_promotion_alert":"","vkexunit_cta_each_option":"","_lightning_design_setting":[],"_jetpack_hide_featured_image":false,"_jetpack_featured_image_duplicate_dismissed":0,"_jetpack_feature_clip_id":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2},"jetpack_post_was_ever_published":false},"categories":[38],"tags":[862,814,99,861,147,956,864,957],"class_list":["post-2708","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-python-memorandum","tag-dataframe","tag-django","tag-mysql","tag-pandas","tag-python","tag-956","tag-864","tag-957"],"veu_head_title_object":{"title":"","add_site_title":""},"jetpack_publicize_connections":[],"jetpack-related-posts":[],"jetpack_sharing_enabled":false,"jetpack_featured_media_url":"https:\/\/qol-kk.com\/wp2\/wp-content\/uploads\/2020\/11\/python.png","_links":{"self":[{"href":"https:\/\/qol-kk.com\/wp2\/wp-json\/wp\/v2\/posts\/2708","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/qol-kk.com\/wp2\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/qol-kk.com\/wp2\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/qol-kk.com\/wp2\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/qol-kk.com\/wp2\/wp-json\/wp\/v2\/comments?post=2708"}],"version-history":[{"count":0,"href":"https:\/\/qol-kk.com\/wp2\/wp-json\/wp\/v2\/posts\/2708\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/qol-kk.com\/wp2\/wp-json\/wp\/v2\/media\/2173"}],"wp:attachment":[{"href":"https:\/\/qol-kk.com\/wp2\/wp-json\/wp\/v2\/media?parent=2708"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/qol-kk.com\/wp2\/wp-json\/wp\/v2\/categories?post=2708"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/qol-kk.com\/wp2\/wp-json\/wp\/v2\/tags?post=2708"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}