我正在执行循环中的API Web抓取功能，并将所有绑定保存在一个文件中。整个工作将涉及许多文件的复制。我希望将“观察时间”（第19列）划分为日期和小时，并且我还希望进行进一步的阅读绘图工作，以便能够识别日期格式的日期列。是否可以在保存CSV之前执行此操作，或者我必须打开CSV文件才能执行此操作？
startDate <- as.Date("01-11-14", format="%d-%m-%y")
endDate <- as.Date("31-01-15",format="%d-%m-%y")
days <- seq(startDate, endDate, "1 day")
lapply(days[1:92], function(day) {
get_sounding_data(
region = "seasia",
date = day,
from_hr = "00",
to_hr = "00",
station_number = "48615")
}) -> soundings_48615
new_df <- map(soundings_48615, . %>% mutate_all(parse_guess))
str(new_df)
library(tidyr)
library(dplyr)
library(xlsx)
dat <- bind_rows(new_df)
write.csv(dat, 'c:/Users/Hp/Documents/yr/climatology/yr_SoundingIndexLowerPart/2014.csv')
get_sounding_data <- NULL
此处在csv中的外观。
... mixing ratio temperature Observation time Precip.
1 18.48 299.23 141102/0000 64.52
2 17.28 298.81 141103/0000 59.4
3 18.65 299.07 141104/0000 61.5
这是数据
str(new_df)
List of 8
$ :'data.frame': 0 obs. of 0 variables
$ :Classes ‘tbl_df’, ‘tbl’ and 'data.frame': 1 obs. of 30 variables:
..$ 1000 hPa to 500 hPa thickness : num 5775
..$ Bulk Richardson Number : num 3003
..$ Bulk Richardson Number using CAPV : num 3325
..$ CAPE using virtual temperature : num 1103
..$ CINS using virtual temperature : num -22.1
..$ Convective Available Potential Energy : num 996
..$ Convective Inhibition : num -31.3
..$ Cross totals index : num 20.9
..$ Equilibrum Level : num 151
..$ Equilibrum Level using virtual temperature : num 151
..$ K index : num 38.7
..$ Level of Free Convection : num 822
..$ LFCT using virtual temperature : num 833
..$ LIFT computed using virtual temperature : num -3.05
..$ Lifted index : num -2.59
..$ Mean mixed layer mixing ratio : num 18.5
..$ Mean mixed layer potential temperature : num 299
..$ Observation time : chr "141102/0000"
..$ Precipitable water [mm] for entire sounding: num 64.5
..$ Pres [hPa] of the Lifted Condensation Level: num 961
..$ Showalter index : num -0.9
..$ Station elevation : num 5
..$ Station identifier : chr "WMKC"
..$ Station latitude : num 6.16
..$ Station longitude : num 102
..$ Station number : int 48615
..$ SWEAT index : num 211
..$ Temp [K] of the Lifted Condensation Level : num 296
..$ Totals totals index : num 44.6
..$ Vertical totals index : num 23.7
$ :Classes ‘tbl_df’, ‘tbl’ and 'data.frame': 1 obs. of 30 variables:
..$ 1000 hPa to 500 hPa thickness : num 5771
..$ Bulk Richardson Number : num 328
..$ Bulk Richardson Number using CAPV : num 395
..$ CAPE using virtual temperature : num 502
..$ CINS using virtual temperature : num -55.3
..$ Convective Available Potential Energy : num 417
..$ Convective Inhibition : num -61.7
..$ Cross totals index : num 21.1
..$ Equilibrum Level : num 167
..$ Equilibrum Level using virtual temperature : num 167
..$ K index : num 35.1
..$ Level of Free Convection : num 826
..$ LFCT using virtual temperature : num 835
..$ LIFT computed using virtual temperature : num -2.38
..$ Lifted index : num -1.98
..$ Mean mixed layer mixing ratio : num 17.3
..$ Mean mixed layer potential temperature : num 299
..$ Observation time : chr "141103/0000"
..$ Precipitable water [mm] for entire sounding: num 59.4
..$ Pres [hPa] of the Lifted Condensation Level: num 952
..$ Showalter index : num -0.65
..$ Station elevation : num 5
..$ Station identifier : chr "WMKC"
..$ Station latitude : num 6.16
..$ Station longitude : num 102
..$ Station number : int 48615
..$ SWEAT index : num 212
..$ Temp [K] of the Lifted Condensation Level : num 295
..$ Totals totals index : num 44.6
..$ Vertical totals index : num 23.5
$ :Classes ‘tbl_df’, ‘tbl’ and 'data.frame': 1 obs. of 30 variables:
..$ 1000 hPa to 500 hPa thickness : num 5775
..$ Bulk Richardson Number : num 431
..$ Bulk Richardson Number using CAPV : num 480
..$ CAPE using virtual temperature : num 1354
..$ CINS using virtual temperature : num -8.6
..$ Convective Available Potential Energy : num 1217
..$ Convective Inhibition : num -11.3
..$ Cross totals index : num 21.7
..$ Equilibrum Level : num 142
..$ Equilibrum Level using virtual temperature : num 142
..$ K index : num 37.4
..$ Level of Free Convection : num 888
..$ LFCT using virtual temperature : num 896
..$ LIFT computed using virtual temperature : num -3.67
..$ Lifted index : num -3.3
..$ Mean mixed layer mixing ratio : num 18.6
..$ Mean mixed layer potential temperature : num 299
..$ Observation time : chr "141104/0000"
..$ Precipitable water [mm] for entire sounding: num 61.5
..$ Pres [hPa] of the Lifted Condensation Level: num 966
..$ Showalter index : num -0.97
..$ Station elevation : num 5
..$ Station identifier : chr "WMKC"
..$ Station latitude : num 6.16
..$ Station longitude : num 102
..$ Station number : int 48615
..$ SWEAT index : num 226
..$ Temp [K] of the Lifted Condensation Level : num 296
..$ Totals totals index : num 44.4
..$ Vertical totals index : num 22.7
$ :Classes ‘tbl_df’, ‘tbl’ and 'data.frame': 1 obs. of 30 variables:
..$ 1000 hPa to 500 hPa thickness : num 5771
..$ Bulk Richardson Number : num 215
..$ Bulk Richardson Number using CAPV : num 236
..$ CAPE using virtual temperature : num 910
..$ CINS using virtual temperature : num -37.2
..$ Convective Available Potential Energy : num 829
..$ Convective Inhibition : num -43.9
..$ Cross totals index : num 21.9
..$ Equilibrum Level : num 168
..$ Equilibrum Level using virtual temperature : num 167
..$ K index : num 39.7
..$ Level of Free Convection : num 829
..$ LFCT using virtual temperature : num 842
..$ LIFT computed using virtual temperature : num -2.68
..$ Lifted index : num -2.43
..$ Mean mixed layer mixing ratio : num 18
..$ Mean mixed layer potential temperature : num 299
..$ Observation time : chr "141105/0000"
..$ Precipitable water [mm] for entire sounding: num 64.9
..$ Pres [hPa] of the Lifted Condensation Level: num 963
..$ Showalter index : num -1.45
..$ Station elevation : num 5
..$ Station identifier : chr "WMKC"
..$ Station latitude : num 6.16
..$ Station longitude : num 102
..$ Station number : int 48615
..$ SWEAT index : num 229
..$ Temp [K] of the Lifted Condensation Level : num 295
..$ Totals totals index : num 45.2
..$ Vertical totals index : num 23.3
$ :Classes ‘tbl_df’, ‘tbl’ and 'data.frame': 1 obs. of 30 variables:
..$ 1000 hPa to 500 hPa thickness : num 5757
..$ Bulk Richardson Number : num 59
..$ Bulk Richardson Number using CAPV : num 70.8
..$ CAPE using virtual temperature : num 546
..$ CINS using virtual temperature : num -51.5
..$ Convective Available Potential Energy : num 455
..$ Convective Inhibition : num -64.1
..$ Cross totals index : num 20
..$ Equilibrum Level : num 194
..$ Equilibrum Level using virtual temperature : num 193
..$ K index : num 35.3
..$ Level of Free Convection : num 808
..$ LFCT using virtual temperature : num 834
..$ LIFT computed using virtual temperature : num -2.24
..$ Lifted index : num -2.04
..$ Mean mixed layer mixing ratio : num 17.3
..$ Mean mixed layer potential temperature : num 299
..$ Observation time : chr "141106/0000"
..$ Precipitable water [mm] for entire sounding: num 59.6
..$ Pres [hPa] of the Lifted Condensation Level: num 949
..$ Showalter index : num 0.42
..$ Station elevation : num 5
..$ Station identifier : chr "WMKC"
..$ Station latitude : num 6.16
..$ Station longitude : num 102
..$ Station number : int 48615
..$ SWEAT index : num 201
..$ Temp [K] of the Lifted Condensation Level : num 295
..$ Totals totals index : num 43.5
..$ Vertical totals index : num 23.5
$ :Classes ‘tbl_df’, ‘tbl’ and 'data.frame': 1 obs. of 30 variables:
..$ 1000 hPa to 500 hPa thickness : num 5777
..$ Bulk Richardson Number : num 80.3
..$ Bulk Richardson Number using CAPV : num 86.5
..$ CAPE using virtual temperature : num 1149
..$ CINS using virtual temperature : num -9.57
..$ Convective Available Potential Energy : num 1067
..$ Convective Inhibition : num -12.4
..$ Cross totals index : num 21.6
..$ Equilibrum Level : num 143
..$ Equilibrum Level using virtual temperature : num 142
..$ K index : num 38.6
..$ Level of Free Convection : num 845
..$ LFCT using virtual temperature : num 901
..$ LIFT computed using virtual temperature : num -3.03
..$ Lifted index : num -2.79
..$ Mean mixed layer mixing ratio : num 18.3
..$ Mean mixed layer potential temperature : num 299
..$ Observation time : chr "141107/0000"
..$ Precipitable water [mm] for entire sounding: num 66
..$ Pres [hPa] of the Lifted Condensation Level: num 965
..$ Showalter index : num -1.15
..$ Station elevation : num 5
..$ Station identifier : chr "WMKC"
..$ Station latitude : num 6.16
..$ Station longitude : num 102
..$ Station number : int 48615
..$ SWEAT index : num 239
..$ Temp [K] of the Lifted Condensation Level : num 296
..$ Totals totals index : num 44.9
..$ Vertical totals index : num 23.3
$ :Classes ‘tbl_df’, ‘tbl’ and 'data.frame': 1 obs. of 30 variables:
..$ 1000 hPa to 500 hPa thickness : num 5775
..$ Bulk Richardson Number : num 29.1
..$ Bulk Richardson Number using CAPV : num 32.7
..$ CAPE using virtual temperature : num 503
..$ CINS using virtual temperature : num -5.45
..$ Convective Available Potential Energy : num 447
..$ Convective Inhibition : num -8.42
..$ Cross totals index : num 20.8
..$ Equilibrum Level : num 197
..$ Equilibrum Level using virtual temperature : num 197
..$ K index : num 35.7
..$ Level of Free Convection : num 871
..$ LFCT using virtual temperature : num 875
..$ LIFT computed using virtual temperature : num -1.07
..$ Lifted index : num -0.9
..$ Mean mixed layer mixing ratio : num 17.7
..$ Mean mixed layer potential temperature : num 298
..$ Observation time : chr "141108/0000"
..$ Precipitable water [mm] for entire sounding: num 65.8
..$ Pres [hPa] of the Lifted Condensation Level: num 966
..$ Showalter index : num 0.29
..$ Station elevation : num 5
..$ Station identifier : chr "WMKC"
..$ Station latitude : num 6.16
..$ Station longitude : num 102
..$ Station number : int 48615
..$ SWEAT index : num 242
..$ Temp [K] of the Lifted Condensation Level : num 295
..$ Totals totals index : num 41.7
..$ Vertical totals index : num 20.9
答案 0 :(得分：2)
是的。使用tidy的{{1}}将一列拆分为原始列的各个段：
seperate这将输出：
library(tidyverse)
df <- tibble(
`Observation time` = c(
'141102/0000',
'141103/0000',
'141104/0000'
)
)
df %>% separate(
col = `Observation time`,
into = c('Date', 'Time'),
sep = '/'
)
请注意，# A tibble: 3 x 2
Date Time
<chr> <chr>
1 141102 0000
2 141103 0000
3 141104 0000
列已删除，并由Observation time和Date取代。如果需要，可以通过Time将它们转换回整数（或其他形式）。
答案 1 :(得分：1)
要将其保存为日期和时间，首先您需要了解日期和时间变量以什么格式存储（Julian time，roman ...等）。然后，我们需要将它们分成两列，如下所示：
library(tidyr)
separate(data = df, col = 'Observation Time', into = c("Date","Time"), sep = "/")