С 201906141930 по «2019-16-14 19:30:00»

Question

У меня есть фрейм данных со столбцом dateHourMinute, который мне нужен как POSIXct для построения графика.

Например, этот dateHourMinute 201906141930, я хотел бы получить: 2019-06-14 19:30:00 как элемент POSIXct.

данные:

structure(list(dateHourMinute = c("201906141930", "201906141931", 
"201906141932", "201906141933", "201906141934", "201906141935", 
"201906141936", "201906141937", "201906141938", "201906141939", 
"201906141940", "201906141941", "201906141942", "201906141943", 
"201906141944", "201906141945", "201906141946", "201906141947", 
"201906141948", "201906141949", "201906141950", "201906141951", 
"201906141952", "201906141953", "201906141954", "201906141955", 
"201906141956", "201906141957", "201906141958", "201906141959", 
"201906142000", "201906142001", "201906142002", "201906142003", 
"201906142004", "201906142005", "201906142006", "201906142007", 
"201906142008", "201906142009", "201906142010", "201906142011", 
"201906142012", "201906142013", "201906142014", "201906142015", 
"201906142016", "201906142017", "201906142018", "201906142019", 
"201906142020", "201906142021", "201906142022", "201906142023", 
"201906142024", "201906142025", "201906142026", "201906142027", 
"201906142028", "201906142029", "201906142030", "201906142031", 
"201906142032", "201906142033", "201906142034", "201906142035", 
"201906142036", "201906142037", "201906142038", "201906142039", 
"201906142040", "201906142041", "201906142042", "201906142043", 
"201906142044", "201906142045", "201906142046", "201906142047", 
"201906142048", "201906142049", "201906142050", "201906142051", 
"201906142052", "201906142053", "201906142054", "201906142055", 
"201906142056", "201906142057", "201906142058", "201906142059", 
"201906142100", "201906142101", "201906142102", "201906142103", 
"201906142104", "201906142105", "201906142106", "201906142107", 
"201906142108", "201906142109", "201906142110", "201906142111", 
"201906142112", "201906142113", "201906142114", "201906142115", 
"201906142116", "201906142117", "201906142118", "201906142119", 
"201906142120", "201906142121", "201906142122", "201906142123", 
"201906142124", "201906142125", "201906142126", "201906142127", 
"201906142128", "201906142129", "201906142130", "201906142131", 
"201906142132", "201906142133", "201906142134", "201906142135", 
"201906142136", "201906142137", "201906142138", "201906142139", 
"201906142140", "201906142141", "201906142142", "201906142143", 
"201906142144", "201906142145", "201906142146", "201906142147", 
"201906142148", "201906142149", "201906142150", "201906142151", 
"201906142152", "201906142153", "201906142154", "201906142155"
), users = c(2894, 2969, 3031, 2912, 2845, 2837, 2832, 2731, 
2784, 2681, 2682, 2614, 2569, 2551, 2580, 2588, 2574, 2458, 2419, 
2504, 2430, 2401, 2322, 2252, 2329, 2374, 2201, 2142, 2163, 2133, 
2087, 2078, 2053, 2206, 2093, 2091, 2045, 2059, 1945, 1943, 1951, 
1972, 1899, 1822, 1841, 1906, 1778, 2148, 3297, 2098, 1801, 1650, 
1630, 1626, 1674, 1647, 1633, 1671, 1757, 1862, 1968, 2045, 2119, 
2396, 2513, 2394, 2375, 2492, 2488, 2381, 2417, 2337, 2243, 2211, 
1999, 2021, 2037, 2418, 2254, 2050, 2004, 1944, 1802, 1718, 1726, 
1725, 1641, 1657, 1592, 1604, 1551, 1553, 1486, 1481, 1518, 1479, 
1310, 1317, 1329, 1259, 1255, 1259, 1407, 1352, 1250, 1250, 1223, 
1149, 1103, 1108, 1025, 1165, 1870, 1452, 1418, 1469, 1522, 1303, 
1147, 1060, 1004, 1001, 1003, 983, 894, 870, 882, 863, 832, 790, 
819, 732, 751, 752, 694, 692, 926, 862, 755, 736, 796, 803, 771, 
869, 745, 709)), row.names = c(NA, -146L), totals = list(list(
    users = "2016665")), minimums = list(list(users = "1")), maximums = list(
    list(users = "11863")), isDataGolden = TRUE, rowCount = 2875L, class = "data.frame")

Answer 1

Вы можете использовать:

df$dateHourMinute <- as.POSIXct(df$dateHourMinute,format = "%Y%m%d%H%M", tz = "UTC")
#Or with `strptime`
#df$dateHourMinute <- strptime(df$dateHourMinute, format = "%Y%m%d%H%M", tz = "UTC")

head(df)
#       dateHourMinute users
#1 2019-06-14 19:30:00  2894
#2 2019-06-14 19:31:00  2969
#3 2019-06-14 19:32:00  3031
#4 2019-06-14 19:33:00  2912
#5 2019-06-14 19:34:00  2845
#6 2019-06-14 19:35:00  2837

Или с lubridate

df$dateHourMinute <- lubridate::ymd_hm(df$dateHourMinute))