使用 dplyr 添加派生条件列
Adding a derived conditional column using dplyr
我正在使用的初始数据集是两家商店的加班塔纳图拉价格列表，一家位于加拿大，另一家位于波兰。
为了公平比较两家商店，我想将波兰兹罗提换算成美元，具体取决于每个数据点当时的汇率。到目前为止，我已经将汇率时间表与狼蛛价格加班合并（参见下面的代码和示例数据）。但是，我不确定如何创建新的派生列，例如“可比价格”，其中以美元计价的价格保持不变，但以波兰兹罗提计价的价格转换为美元。我尝试使用 mutate 函数创建一个新列，其中价格列除以转换率，但我正在努力如何仅对 Zloty 中的行设置此条件。
这是要查找的输出 ID 类型的示例：
Date
1 USD to PLN
Price
Currency
Converted
2013-06-07
3.241658
10
$
10
2013-06-07
3.241658
20
zl
6.17
library(priceR)
library(dplyr)
Tarantula <- structure(list(Date = structure(c(15863, 16355, 15930, 15962,
15903, 16121, 16545, 16575, 16608, 16000, 16639, 16670, 16306,
16249, 17956, 17988, 18019, 18050, 18111, 18143, 17819, 17646,
17676, 17707, 17738, 17648, 17770, 17801, 17679, 17710, 17740,
17833, 17864, 17926, 17895, 18188, 17646, 17676, 17707, 17738,
17648, 17770, 17679, 17710, 17740, 17833, 17864, 17895, 17444,
17478, 17387, 17419, 17512, 17542, 17391, 17455, 17489, 17492,
17584, 17554, 17523, 17433, 17435, 17465, 17526, 17405, 17559,
17467, 17438, 17500, 15962, 15962, 18111, 18081, 18143, 18918,
18188, 18578, 18689, 18708, 18923, 18897, 18578, 18689, 18708,
17444, 17478, 17387, 17418, 17512, 17542, 17433, 17391, 17455,
18918, 17489, 17584, 17492, 17554, 18923, 17523, 17646, 17435,
17465, 17526, 17648, 17405, 18897, 17559, 17467, 17438, 17500,
18578, 18689, 18708, 18923, 18897, 16355, 16545, 16575, 16306,
16249, 18081, 16846, 16702, 17956, 18111, 18111, 18081, 18143,
18143, 17819, 18188, 18188, 17738, 17770, 17801, 17740, 17833,
17864, 17926, 17895, 17801, 17167, 17444, 17478, 17387, 17419,
17391, 17180, 17300, 17331, 17362, 17455, 17121, 17122, 17489,
17492, 17433, 17435, 17465, 17405, 17467, 17438, 17500, 16996,
17028, 17059, 17090, 16969, 17646, 17676, 17707, 17738, 17648,
17770, 17679, 17710, 17740, 17646, 17988, 18019, 18050, 16608,
16639, 16867, 17331, 16846, 17362, 16876, 16908, 16939, 17167,
17180, 17121, 17122, 17444, 17478, 17387, 17418, 17512, 17542,
17433, 17391, 17455, 18918, 17489, 17492, 17554, 18923, 17523,
17435, 17465, 17526, 17405, 18897, 17559, 17467, 17438, 17500,
16545, 16575, 16608, 16639, 16670, 16121, 17478, 17512, 17542,
18111, 18143, 17300, 17489, 17492, 17554, 17523, 17676, 17707,
17526, 17559, 17679, 17500, 17710, 16355, 18111, 18081, 18143,
18188, 18578, 18689, 18918, 18708, 18923, 18897, 18918, 18923,
18897, 17387, 18578, 17391, 17405, 18923, 18897, 18578, 18689,
18708, 16867, 16876, 16908, 16969, 16939, 18578, 18689, 18918,
18708, 18923, 18897, 17988, 17988, 18019, 18050, 18111, 18081,
18143, 18578, 18689, 17819, 18188, 18708, 17770, 17801, 17833,
17864, 17926, 17895, 15863, 17956, 17988, 18019, 18050, 18111,
18081, 18143, 15930, 17819, 15903, 18188, 17646, 17676, 17738,
17648, 17770, 17801, 17710, 17740, 17833, 17864, 17926, 17895,
17444, 17478, 17512, 17542, 18578, 18689, 17455, 18918, 17489,
17584, 18708, 17492, 17554, 18923, 17523, 17435, 17465, 17526,
18897, 17559, 17467, 17438, 17500, 17801, 17444, 17478, 17512,
17542, 18578, 18689, 17433, 17819, 17455, 18918, 18188, 17489,
17584, 18708, 17492, 17554, 18923, 17523, 17646, 17676, 17707,
17738, 17435, 17465, 17526, 17648, 17770, 17801, 18897, 17559,
17679, 17710, 17740, 17467, 17438, 17833, 17864, 17926, 17500,
17895, 17956, 17988, 18019, 18050, 18111, 18081, 18143, 18578,
18689, 17819, 18918, 18188, 18708, 18923, 17770, 17801, 18897,
17833, 17864, 17926, 17895, 17444, 17478, 17512, 17542, 17956,
17988, 18019, 18050, 18081, 18578, 18689, 17433, 17819, 17455,
17489, 17584, 18708, 17492, 17554, 17523, 17646, 17676, 17707,
17738, 17435, 17465, 17526, 17648, 17770, 17801, 17559, 17679,
17710, 17740, 17467, 17438, 17833, 17864, 17926, 17500, 17895,
16355, 18689, 16545, 16575, 18708, 16608, 16639, 16670, 18923,
16702, 18897, 17167, 18689, 17090, 17121, 17122, 18918, 16121,
18708, 18923, 16306, 18897, 16249, 16121, 18923, 18897, 18689,
18918, 18708, 16867, 16996, 16846, 16876, 16908, 16939, 17980,
18923, 18578, 18689, 16996, 17090, 16969, 16939, 18918, 18188,
18708, 18923, 18897, 15962, 16121, 16000, 18578, 18689, 18708,
17331, 17362, 16306, 17444, 17478, 17387, 17419, 17512, 17542,
17391, 17300, 17331, 16996, 17362, 17455, 16908, 16969, 16939,
17489, 17492, 17584, 17554, 17523, 17433, 17646, 17676, 17707,
17980, 17646, 17738, 17435, 17465, 17526, 17648, 17405, 17770,
17559, 17679, 17710, 17740, 17467, 17438, 17500, 15930, 15962,
16121, 16000, 16306, 16249, 15863, 15863, 16355, 15930, 15930,
15962, 15903, 15903, 16121, 16000, 16306, 16249, 18923, 18897,
17956, 17988, 18019, 18050, 18111, 18081, 18143, 15962, 17819,
18188, 16121, 16000, 17770, 17801, 17833, 17864, 17926, 17895,
18578, 18689, 18918, 18708, 18923, 18897, 18578, 18689, 18918,
18708, 18923, 18897, 18923, 18897, 16846, 16876, 16306, 17419,
17391, 17405, 16249, 18019, 18050, 18111, 18081, 18143, 18188,
18923, 18578, 18689, 18918, 18708, 16996, 16969, 16939, 17167,
17478, 17090, 17121, 17122, 17489, 17492, 17500, 17444, 17478,
17512, 17542, 17455, 17489, 17584, 17492, 17554, 17523, 17435,
17465, 17526, 17559, 17467, 17438, 17500, 17956, 17988, 18019,
18050, 18081, 17819, 17646, 17676, 17707, 17738, 17648, 17770,
17801, 17679, 17710, 17740, 17833, 17864, 17926, 17895, 18111,
18143, 18188, 18578, 18689, 18918, 18708, 18923, 18897, 18578,
18689, 17819, 18918, 18708, 18923, 17770, 17801, 18897, 17833,
17864, 17926, 17895, 18578, 18689, 18918, 18708, 18923, 18897,
17956, 17988, 18019, 18050, 18111, 18081, 18143, 18578, 18689,
17819, 18188, 18708, 17770, 17801, 17833, 17864, 17926, 17895,
16939, 17444, 17419, 17391, 17455, 17433, 17435, 17405, 17438,
18019, 18050, 18111, 18081, 18143, 17387, 17418, 17391, 17405,
16876, 16908, 18689, 18708, 16306, 16249, 18923, 18918, 18923,
18897, 15962, 17988, 17819, 17646, 17676, 17707, 17738, 17648,
17770, 17801, 17679, 17710, 17740, 17833, 17864, 17926, 17895,
15863, 15930, 15962, 15903, 16121, 16000, 18111, 18143, 17646,
17676, 17707, 17738, 17648, 17679, 17710, 17740, 18918, 18923,
18897, 18923, 18897, 18923, 18897, 17551, 17883, 17486, 17456,
17427, 17610, 17551, 17518, 17486, 17456, 17427, 17610, 17551,
17610, 17427, 17456, 17427, 19051, 17551, 17518, 17486, 17610,
17551, 17518, 17486, 17456, 17427, 17486, 17456, 17427, 17551,
17518, 17486, 17456, 17427, 17551, 17518, 17486, 17427, 17610,
17610, 17456, 19051), class = "Date"), Price = c(10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L,
100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L,
100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L,
100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L,
100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 14L,
15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L,
15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L,
15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L,
15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L,
15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L,
15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 175L, 175L, 175L, 175L,
175L, 175L, 175L, 175L, 175L, 175L, 175L, 175L, 175L, 175L, 175L,
175L, 175L, 175L, 175L, 175L, 175L, 175L, 175L, 175L, 20L, 20L,
20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L,
20L, 20L, 20L, 20L, 20L, 20L, 20L, 200L, 200L, 200L, 200L, 200L,
200L, 200L, 200L, 200L, 200L, 200L, 200L, 200L, 200L, 200L, 200L,
200L, 200L, 200L, 200L, 200L, 225L, 225L, 225L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 250L, 250L, 250L, 250L, 250L, 250L, 250L, 250L, 250L, 250L,
250L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L,
30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L,
30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L,
30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 35L, 35L, 35L, 35L,
35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L,
35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L,
35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L,
35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L,
35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 40L, 40L, 40L, 40L, 40L,
40L, 40L, 40L, 40L, 40L, 40L, 45L, 45L, 45L, 45L, 45L, 45L, 45L,
45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L,
45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L,
45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L,
45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L,
45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L,
45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L,
45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 50L,
50L, 50L, 50L, 50L, 50L, 50L, 50L, 50L, 50L, 50L, 50L, 55L, 55L,
60L, 65L, 65L, 65L, 65L, 65L, 65L, 65L, 65L, 65L, 65L, 65L, 65L,
65L, 65L, 65L, 65L, 75L, 75L, 75L, 75L, 75L, 75L, 75L, 75L, 75L,
75L, 75L, 75L, 75L, 75L, 75L, 75L, 75L, 75L, 75L, 75L, 75L, 85L,
85L, 100L, 100L, 100L, 100L, 100L, 110L, 110L, 110L, 110L, 120L,
120L, 125L, 125L, 13L, 150L, 15L, 15L, 200L, 20L, 20L, 20L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 30L, 30L, 30L, 30L, 30L,
30L, 30L, 30L, 30L, 35L, 35L, 40L, 90L), Currency = c("$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "zl", "zl", "zl", "zl", "zl", "zl",
"zl", "zl", "zl", "zl", "zl", "zl", "zl", "zl", "zl", "zl", "zl",
"zl", "zl", "zl", "zl", "zl", "zl", "zl", "zl", "zl", "zl", "zl",
"zl", "zl", "zl", "zl", "zl", "zl", "zl", "zl", "zl", "zl", "zl",
"zl", "zl", "zl", "zl")), class = "data.frame", row.names = c(NA,
-817L))
#Getting exchange rates from USD to PLN from 2013 to 2019
cur <- historical_exchange_rates("USD", to = "PLN",
start_date = "2013-01-01", end_date = "2022-03-01")
colnames(cur) <- c('Date','1_USD_to_PLN') #changing column names.
#making sure the date columns are formatted as dates
cur$Date <- as.Date(cur$Date, format = "%Y.%m.%d")
Tarantula$Date <- as.Date(Tarantula$Date)
#merging the two datasets together for rows where they share a date
merged <- right_join(cur, Tarantula, by = "Date")
我想在与 dplyr 玩了一会儿之后我已经设法回答了我自己的问题！
以前我试过这个：
converted <- mutate(merged, Converted = ifelse(merged$Currency=="$", (merged$Price), (merged$Price/merged_USD_to_PLN)))
并且还尝试在 1_USD_to_PLN 周围添加语音标记，但两者都返回错误。
虽然这现在似乎有效：
converted <- mutate(merged, Converted = ifelse(merged$Currency=="$", (merged$Price), (merged$Price/merged[,2])))
以及完整代码：
Tarantula <- read.csv("Tarantula_Data.csv")
#Getting exchange rates from USD to PLN from 2013 to 2019
cur <- historical_exchange_rates("USD", to = "PLN",
start_date = "2013-01-01", end_date = "2022-03-01")
colnames(cur) <- c('Date','1_USD_to_PLN') #changing column names
#making sure the date columns are formatted as dates
cur$Date <- as.Date(cur$Date, format = "%Y.%m.%d")
Tarantula$Date <- as.Date(Tarantula$Date)
#merging the two datasets together for rows where they share a date
merged <- right_join(cur, Tarantula, by = "Date")
as.factor(merged$Currency)
converted <- mutate(merged, Converted = ifelse(merged$Currency=="$", (merged$Price), (merged$Price/merged[,2])))
您还可以使用 case_when()，它允许您在 mutate() 中执行逻辑语句，如果您有更多条件，将来可能会有用：
library(dplyr)
converted <- merged %>%
mutate(Conversion=as.numeric(`1_USD_to_PLN`),
Price=as.numeric(Price),
comparable=case_when(
Currency=="$" ~ Price,
Currency=="zl" ~ Price/Conversion
))
另请注意，您可以使用一对反引号 (`) 来指代保留的或非法的名称或符号组合。
我正在使用的初始数据集是两家商店的加班塔纳图拉价格列表，一家位于加拿大，另一家位于波兰。
为了公平比较两家商店，我想将波兰兹罗提换算成美元，具体取决于每个数据点当时的汇率。到目前为止，我已经将汇率时间表与狼蛛价格加班合并（参见下面的代码和示例数据）。但是，我不确定如何创建新的派生列，例如“可比价格”，其中以美元计价的价格保持不变，但以波兰兹罗提计价的价格转换为美元。我尝试使用 mutate 函数创建一个新列，其中价格列除以转换率，但我正在努力如何仅对 Zloty 中的行设置此条件。
这是要查找的输出 ID 类型的示例：
| Date | 1 USD to PLN | Price | Currency | Converted |
|---|---|---|---|---|
| 2013-06-07 | 3.241658 | 10 | $ | 10 |
| 2013-06-07 | 3.241658 | 20 | zl | 6.17 |
library(priceR)
library(dplyr)
Tarantula <- structure(list(Date = structure(c(15863, 16355, 15930, 15962,
15903, 16121, 16545, 16575, 16608, 16000, 16639, 16670, 16306,
16249, 17956, 17988, 18019, 18050, 18111, 18143, 17819, 17646,
17676, 17707, 17738, 17648, 17770, 17801, 17679, 17710, 17740,
17833, 17864, 17926, 17895, 18188, 17646, 17676, 17707, 17738,
17648, 17770, 17679, 17710, 17740, 17833, 17864, 17895, 17444,
17478, 17387, 17419, 17512, 17542, 17391, 17455, 17489, 17492,
17584, 17554, 17523, 17433, 17435, 17465, 17526, 17405, 17559,
17467, 17438, 17500, 15962, 15962, 18111, 18081, 18143, 18918,
18188, 18578, 18689, 18708, 18923, 18897, 18578, 18689, 18708,
17444, 17478, 17387, 17418, 17512, 17542, 17433, 17391, 17455,
18918, 17489, 17584, 17492, 17554, 18923, 17523, 17646, 17435,
17465, 17526, 17648, 17405, 18897, 17559, 17467, 17438, 17500,
18578, 18689, 18708, 18923, 18897, 16355, 16545, 16575, 16306,
16249, 18081, 16846, 16702, 17956, 18111, 18111, 18081, 18143,
18143, 17819, 18188, 18188, 17738, 17770, 17801, 17740, 17833,
17864, 17926, 17895, 17801, 17167, 17444, 17478, 17387, 17419,
17391, 17180, 17300, 17331, 17362, 17455, 17121, 17122, 17489,
17492, 17433, 17435, 17465, 17405, 17467, 17438, 17500, 16996,
17028, 17059, 17090, 16969, 17646, 17676, 17707, 17738, 17648,
17770, 17679, 17710, 17740, 17646, 17988, 18019, 18050, 16608,
16639, 16867, 17331, 16846, 17362, 16876, 16908, 16939, 17167,
17180, 17121, 17122, 17444, 17478, 17387, 17418, 17512, 17542,
17433, 17391, 17455, 18918, 17489, 17492, 17554, 18923, 17523,
17435, 17465, 17526, 17405, 18897, 17559, 17467, 17438, 17500,
16545, 16575, 16608, 16639, 16670, 16121, 17478, 17512, 17542,
18111, 18143, 17300, 17489, 17492, 17554, 17523, 17676, 17707,
17526, 17559, 17679, 17500, 17710, 16355, 18111, 18081, 18143,
18188, 18578, 18689, 18918, 18708, 18923, 18897, 18918, 18923,
18897, 17387, 18578, 17391, 17405, 18923, 18897, 18578, 18689,
18708, 16867, 16876, 16908, 16969, 16939, 18578, 18689, 18918,
18708, 18923, 18897, 17988, 17988, 18019, 18050, 18111, 18081,
18143, 18578, 18689, 17819, 18188, 18708, 17770, 17801, 17833,
17864, 17926, 17895, 15863, 17956, 17988, 18019, 18050, 18111,
18081, 18143, 15930, 17819, 15903, 18188, 17646, 17676, 17738,
17648, 17770, 17801, 17710, 17740, 17833, 17864, 17926, 17895,
17444, 17478, 17512, 17542, 18578, 18689, 17455, 18918, 17489,
17584, 18708, 17492, 17554, 18923, 17523, 17435, 17465, 17526,
18897, 17559, 17467, 17438, 17500, 17801, 17444, 17478, 17512,
17542, 18578, 18689, 17433, 17819, 17455, 18918, 18188, 17489,
17584, 18708, 17492, 17554, 18923, 17523, 17646, 17676, 17707,
17738, 17435, 17465, 17526, 17648, 17770, 17801, 18897, 17559,
17679, 17710, 17740, 17467, 17438, 17833, 17864, 17926, 17500,
17895, 17956, 17988, 18019, 18050, 18111, 18081, 18143, 18578,
18689, 17819, 18918, 18188, 18708, 18923, 17770, 17801, 18897,
17833, 17864, 17926, 17895, 17444, 17478, 17512, 17542, 17956,
17988, 18019, 18050, 18081, 18578, 18689, 17433, 17819, 17455,
17489, 17584, 18708, 17492, 17554, 17523, 17646, 17676, 17707,
17738, 17435, 17465, 17526, 17648, 17770, 17801, 17559, 17679,
17710, 17740, 17467, 17438, 17833, 17864, 17926, 17500, 17895,
16355, 18689, 16545, 16575, 18708, 16608, 16639, 16670, 18923,
16702, 18897, 17167, 18689, 17090, 17121, 17122, 18918, 16121,
18708, 18923, 16306, 18897, 16249, 16121, 18923, 18897, 18689,
18918, 18708, 16867, 16996, 16846, 16876, 16908, 16939, 17980,
18923, 18578, 18689, 16996, 17090, 16969, 16939, 18918, 18188,
18708, 18923, 18897, 15962, 16121, 16000, 18578, 18689, 18708,
17331, 17362, 16306, 17444, 17478, 17387, 17419, 17512, 17542,
17391, 17300, 17331, 16996, 17362, 17455, 16908, 16969, 16939,
17489, 17492, 17584, 17554, 17523, 17433, 17646, 17676, 17707,
17980, 17646, 17738, 17435, 17465, 17526, 17648, 17405, 17770,
17559, 17679, 17710, 17740, 17467, 17438, 17500, 15930, 15962,
16121, 16000, 16306, 16249, 15863, 15863, 16355, 15930, 15930,
15962, 15903, 15903, 16121, 16000, 16306, 16249, 18923, 18897,
17956, 17988, 18019, 18050, 18111, 18081, 18143, 15962, 17819,
18188, 16121, 16000, 17770, 17801, 17833, 17864, 17926, 17895,
18578, 18689, 18918, 18708, 18923, 18897, 18578, 18689, 18918,
18708, 18923, 18897, 18923, 18897, 16846, 16876, 16306, 17419,
17391, 17405, 16249, 18019, 18050, 18111, 18081, 18143, 18188,
18923, 18578, 18689, 18918, 18708, 16996, 16969, 16939, 17167,
17478, 17090, 17121, 17122, 17489, 17492, 17500, 17444, 17478,
17512, 17542, 17455, 17489, 17584, 17492, 17554, 17523, 17435,
17465, 17526, 17559, 17467, 17438, 17500, 17956, 17988, 18019,
18050, 18081, 17819, 17646, 17676, 17707, 17738, 17648, 17770,
17801, 17679, 17710, 17740, 17833, 17864, 17926, 17895, 18111,
18143, 18188, 18578, 18689, 18918, 18708, 18923, 18897, 18578,
18689, 17819, 18918, 18708, 18923, 17770, 17801, 18897, 17833,
17864, 17926, 17895, 18578, 18689, 18918, 18708, 18923, 18897,
17956, 17988, 18019, 18050, 18111, 18081, 18143, 18578, 18689,
17819, 18188, 18708, 17770, 17801, 17833, 17864, 17926, 17895,
16939, 17444, 17419, 17391, 17455, 17433, 17435, 17405, 17438,
18019, 18050, 18111, 18081, 18143, 17387, 17418, 17391, 17405,
16876, 16908, 18689, 18708, 16306, 16249, 18923, 18918, 18923,
18897, 15962, 17988, 17819, 17646, 17676, 17707, 17738, 17648,
17770, 17801, 17679, 17710, 17740, 17833, 17864, 17926, 17895,
15863, 15930, 15962, 15903, 16121, 16000, 18111, 18143, 17646,
17676, 17707, 17738, 17648, 17679, 17710, 17740, 18918, 18923,
18897, 18923, 18897, 18923, 18897, 17551, 17883, 17486, 17456,
17427, 17610, 17551, 17518, 17486, 17456, 17427, 17610, 17551,
17610, 17427, 17456, 17427, 19051, 17551, 17518, 17486, 17610,
17551, 17518, 17486, 17456, 17427, 17486, 17456, 17427, 17551,
17518, 17486, 17456, 17427, 17551, 17518, 17486, 17427, 17610,
17610, 17456, 19051), class = "Date"), Price = c(10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L,
100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L,
100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L,
100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L,
100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 100L, 14L,
15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L,
15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L,
15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L,
15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L,
15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L,
15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 175L, 175L, 175L, 175L,
175L, 175L, 175L, 175L, 175L, 175L, 175L, 175L, 175L, 175L, 175L,
175L, 175L, 175L, 175L, 175L, 175L, 175L, 175L, 175L, 20L, 20L,
20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L, 20L,
20L, 20L, 20L, 20L, 20L, 20L, 20L, 200L, 200L, 200L, 200L, 200L,
200L, 200L, 200L, 200L, 200L, 200L, 200L, 200L, 200L, 200L, 200L,
200L, 200L, 200L, 200L, 200L, 225L, 225L, 225L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 250L, 250L, 250L, 250L, 250L, 250L, 250L, 250L, 250L, 250L,
250L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L,
30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L,
30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L,
30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 35L, 35L, 35L, 35L,
35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L,
35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L,
35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L,
35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L,
35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 40L, 40L, 40L, 40L, 40L,
40L, 40L, 40L, 40L, 40L, 40L, 45L, 45L, 45L, 45L, 45L, 45L, 45L,
45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L,
45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L,
45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L,
45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L,
45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L,
45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L,
45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 45L, 50L,
50L, 50L, 50L, 50L, 50L, 50L, 50L, 50L, 50L, 50L, 50L, 55L, 55L,
60L, 65L, 65L, 65L, 65L, 65L, 65L, 65L, 65L, 65L, 65L, 65L, 65L,
65L, 65L, 65L, 65L, 75L, 75L, 75L, 75L, 75L, 75L, 75L, 75L, 75L,
75L, 75L, 75L, 75L, 75L, 75L, 75L, 75L, 75L, 75L, 75L, 75L, 85L,
85L, 100L, 100L, 100L, 100L, 100L, 110L, 110L, 110L, 110L, 120L,
120L, 125L, 125L, 13L, 150L, 15L, 15L, 200L, 20L, 20L, 20L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 30L, 30L, 30L, 30L, 30L,
30L, 30L, 30L, 30L, 35L, 35L, 40L, 90L), Currency = c("$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
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"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
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"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
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"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$", "$",
"$", "$", "$", "$", "$", "zl", "zl", "zl", "zl", "zl", "zl",
"zl", "zl", "zl", "zl", "zl", "zl", "zl", "zl", "zl", "zl", "zl",
"zl", "zl", "zl", "zl", "zl", "zl", "zl", "zl", "zl", "zl", "zl",
"zl", "zl", "zl", "zl", "zl", "zl", "zl", "zl", "zl", "zl", "zl",
"zl", "zl", "zl", "zl")), class = "data.frame", row.names = c(NA,
-817L))
#Getting exchange rates from USD to PLN from 2013 to 2019
cur <- historical_exchange_rates("USD", to = "PLN",
start_date = "2013-01-01", end_date = "2022-03-01")
colnames(cur) <- c('Date','1_USD_to_PLN') #changing column names.
#making sure the date columns are formatted as dates
cur$Date <- as.Date(cur$Date, format = "%Y.%m.%d")
Tarantula$Date <- as.Date(Tarantula$Date)
#merging the two datasets together for rows where they share a date
merged <- right_join(cur, Tarantula, by = "Date")
我想在与 dplyr 玩了一会儿之后我已经设法回答了我自己的问题！
以前我试过这个：
converted <- mutate(merged, Converted = ifelse(merged$Currency=="$", (merged$Price), (merged$Price/merged_USD_to_PLN)))
并且还尝试在 1_USD_to_PLN 周围添加语音标记，但两者都返回错误。
虽然这现在似乎有效：
converted <- mutate(merged, Converted = ifelse(merged$Currency=="$", (merged$Price), (merged$Price/merged[,2])))
以及完整代码：
Tarantula <- read.csv("Tarantula_Data.csv")
#Getting exchange rates from USD to PLN from 2013 to 2019
cur <- historical_exchange_rates("USD", to = "PLN",
start_date = "2013-01-01", end_date = "2022-03-01")
colnames(cur) <- c('Date','1_USD_to_PLN') #changing column names
#making sure the date columns are formatted as dates
cur$Date <- as.Date(cur$Date, format = "%Y.%m.%d")
Tarantula$Date <- as.Date(Tarantula$Date)
#merging the two datasets together for rows where they share a date
merged <- right_join(cur, Tarantula, by = "Date")
as.factor(merged$Currency)
converted <- mutate(merged, Converted = ifelse(merged$Currency=="$", (merged$Price), (merged$Price/merged[,2])))
您还可以使用 case_when()，它允许您在 mutate() 中执行逻辑语句，如果您有更多条件，将来可能会有用：
library(dplyr)
converted <- merged %>%
mutate(Conversion=as.numeric(`1_USD_to_PLN`),
Price=as.numeric(Price),
comparable=case_when(
Currency=="$" ~ Price,
Currency=="zl" ~ Price/Conversion
))
另请注意，您可以使用一对反引号 (`) 来指代保留的或非法的名称或符号组合。