使用 dplyr 添加派生条件列

发布于 2025-01-12 18:44:19 字数 15636 浏览 0 评论 0原文

我正在使用的初始数据集是两家商店的塔纳图拉加班价格列表，一家位于加拿大，另一家位于波兰。

为了在两家商店之间进行公平比较，我想根据每个数据点时的汇率将波兰兹罗提转换为美元。到目前为止，我已经将汇率时间表与狼蛛价格加班合并起来（请参阅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”，其中美元价格保持不变，但 PLN 价格转换为美元。我尝试使用 mutate 函数创建一个新列，其中价格列除以转化率，但我正在努力如何仅针对兹罗提中的行设置此条件。

这是要查找的输出 id 类型的示例：

日期	1 USD 到 PLN	价格	货币	转换
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")

原文

The initial dataset I am working with is a list of tarnatula prices overtime from two shops, one based in Canada and the other in Poland.

In order to make a fair comparison between the two shops, I want to convert the Polish Zloty to USD, depending on the exchange rate at the time of each data point. So far I've merged a timeline of exchange rates with tarantula prices overtime (See code below with sample data). However, Im unsure how to create a new derived column, e.g. "Comparible prices" where the prices already in USD remain the same but those in PLN are converted to USD. Ive tried to use the mutate function to create a new column where the price column is divided by the conversion rate, but am struggling how to make this conditional for the rows in Zloty only.

This is an example of the kind of output id be looking for:

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, 
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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, 
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17512, 17542, 17455, 17489, 17584, 17492, 17554, 17523, 17435, 
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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, 
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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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quot;, "quot;, "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")

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一口甜 2025-01-19 18:44:19

您还可以使用 case_when() 它可以让您在 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 (`) 来引用否则保留或非法的名称或符号组合。

You could also use case_when() which lets you do logical statements in a mutate() and might be useful in the future if you have more conditions:

library(dplyr)

converted <- merged %>% 
  mutate(Conversion=as.numeric(`1_USD_to_PLN`),
         Price=as.numeric(Price),
         comparable=case_when(
           Currency=="quot; ~ Price,
           Currency=="zl" ~ Price/Conversion
         ))

Also as a note, you can use a pair of backticks (`) to refer to names or combinations of symbols that are otherwise reserved or illegal.

回复收藏 0 原文

清君侧 2025-01-19 18:44:19

我想在与 dplyr 玩了一段时间后我已经成功回答了我自己的问题！

之前我尝试过这个：

converted <- mutate(merged, Converted = ifelse(merged$Currency=="$", (merged$Price), (merged$Price/merged$1_USD_to_PLN)))

并且还尝试了 1_USD_to_PLN 周围的语音标记，但这两个都返回了错误。

现在这似乎有效：

converted <- mutate(merged, Converted = ifelse(merged$Currency=="$", (merged$Price), (merged$Price/merged[,2])))

完整的代码：

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])))

I think I've managed to answer my own question after a bit of playing round with dplyr!

Previously I had tried this:

converted <- mutate(merged, Converted = ifelse(merged$Currency=="quot;, (merged$Price), (merged$Price/merged$1_USD_to_PLN)))

And also tried it with speech marks around the 1_USD_to_PLN, but both of these returned an error.

This now seems to be working though:

converted <- mutate(merged, Converted = ifelse(merged$Currency=="quot;, (merged$Price), (merged$Price/merged[,2])))

And the full code:

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$Currency=="quot;, (merged$Price), (merged$Price/merged[,2])))

回复收藏 0 原文

~没有更多了~