R ggplot色带颜色变化取决于y轴可变的值_R_Ggplot2

R ggplot色带颜色变化取决于y轴可变的值

R ggplot色带颜色变化取决于y轴可变的值,r,ggplot2,R,Ggplot2,我试图绘制12个月期间两个项目的两个销售时间序列图（下面的子集）。每种商品的销售都会受到其他产品促销条件的影响，有时（由于季节性），这会导致销售额下降，而有时它会实际促进销售额。为了表示这一点，我创建了两个折线图，它们是面包装的。在每一个方面，我们都有一组商品销售（y=销售）和它的交叉效应（y=交叉效应；虚线），它显示了反向促销对销售的影响，在这两条线之间，我有一条色带，用粉蓝填充空白，以显示其重要性。允许ylim随数据输入而变化。我不确定如何解决这些问题：是否可以使色带和/或交叉效应线的颜

我试图绘制12个月期间两个项目的两个销售时间序列图（下面的子集）。每种商品的销售都会受到其他产品促销条件的影响，有时（由于季节性），这会导致销售额下降，而有时它会实际促进销售额。为了表示这一点，我创建了两个折线图，它们是面包装的。在每一个方面，我们都有一组商品销售（y=销售）和它的交叉效应（y=交叉效应；虚线），它显示了反向促销对销售的影响，在这两条线之间，我有一条色带，用粉蓝填充空白，以显示其重要性。允许ylim随数据输入而变化。我不确定如何解决这些问题：

是否可以使色带和/或交叉效应线的颜色变化，即绿色表示增加，红色表示减少

如果最大值为100，我如何将Y销售额四舍五入到10秒；如果最大值低于1000，我如何将Y销售额四舍五入到100秒。。。高达10万秒

感谢您抽出时间阅读我的问题！：斯迈利：

这里是一些玩具数据和我的一个尝试

my_breaks <- function(x){seq(min(0), max(x), length.out = 5)}
my_labels <- function(x){round(x, digits = 0)}
Prop_change_df %>%
  mutate(cross_effect = as.integer(cross_effect))%>%
  mutate(cross_eff_gp = as.factor(if_else(cross_effect > Sales, "Lift", "Decline"))) %>%
  ggplot(aes(x = day, group = Items)) +
  geom_ribbon(aes(ymin=Sales, ymax=cross_effect, fill = Sales - cross_effect > 0), fill = "powderblue")+
  geom_line(aes(y  = Sales, colour = interaction(Items, cross_eff_gp)), size = 0.25) +
  geom_line(aes(y  = cross_effect), size = 0.25, linetype="twodash", colour = "#F8766D") +
  facet_wrap(~ Items, scales = 'free', nrow = 2) +
  scale_y_continuous(breaks = my_breaks, labels = my_labels) +
  scale_fill_manual(values=c("turquoise4","green1","turquoise4","darkgreen"))

    structure(list(day = structure(c(1546300800, 1547078400, 1554850800, 
    1554937200, 1555023600, 1555110000, 1555196400, 1555282800, 1555369200, 
    1555455600, 1555542000, 1555628400, 1547164800, 1555714800, 1555801200, 
    1555887600, 1555974000, 1556060400, 1556146800, 1556233200, 1556319600, 
    1556406000, 1556492400, 1547251200, 1556578800, 1556665200, 1556751600, 
    1556838000, 1556924400, 1557010800, 1557097200, 1557183600, 1557270000, 
    1557356400, 1547337600, 1557442800, 1557529200, 1557615600, 1557702000, 
    1557788400, 1557874800, 1557961200, 1558047600, 1558134000, 1558220400, 
    1547424000, 1558306800, 1558393200, 1558479600, 1558566000, 1558652400, 
    1558738800, 1558825200, 1558911600, 1558998000, 1559084400, 1547510400, 
    1559170800, 1559257200, 1559343600), tzone = "", class = c("POSIXct", 
    "POSIXt")), rowname = c("1", "10", "100", "101", "102", "103", 
    "104", "105", "106", "107", "108", "109", "11", "110", "111", 
    "112", "113", "114", "115", "116", "117", "118", "119", "12", 
    "120", "121", "122", "123", "124", "125", "126", "127", "128", 
    "129", "13", "130", "131", "132", "133", "134", "135", "136", 
    "137", "138", "139", "14", "140", "141", "142", "143", "144", 
    "145", "146", "147", "148", "149", "15", "150", "151", "152"), 
        Items = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
        1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
        1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
        1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
        1L, 1L, 1L, 1L, 1L), .Label = c("ITEMA", "ITEMB"), class = "factor"), 
        Sales = c(344L, 250L, 316L, 187L, 196L, 151L, 236L, 170L, 
        137L, 231L, 258L, 194L, 327L, 300L, 144L, 240L, 196L, 222L,
    292L, 215L, 241L, 210L, 156L, 408L, 151L, 137L, 168L, 172L, 
    203L, 186L, 197L, 148L, 154L, 139L, 363L, 136L, 183L, 177L, 
    130L, 141L, 132L, 144L, 143L, 152L, 165L, 402L, 128L, 133L, 
    163L, 113L, 164L, 171L, 162L, 116L, 117L, 128L, 432L, 107L, 
    125L, 187L), z_diff_HC = c(15.5644333787362, 1.87906641317019, 
    12.557755209854, 14.8812985333839, 17.5223825569917, 23.8360074736518, 
    18.7410953048883, 14.9583507793006, 13.9273511861036, -3.51818494122973, 
    12.1544583602306, 3.02440323681235, 3.82962965039171, 17.5478815812969, 
    3.3229377520704, 0.633981373873377, 9.27905096386199, 12.5799626114306, 
    14.2247591638052, 16.6487747981391, 15.8304549924645, 9.15979751528926, 
    15.0129291111416, -0.688334784614703, -7.63226366995004, 
    0.428951331549642, 10.2702773598704, 36.1219319585148, 15.4142833246758, 
    4.88470834307489, 21.2490429809954, -7.33361550396995, -4.29869918645501, 
    18.9489364038734, -1.76460720804452, -1.35823311958288, 34.6935883900468, 
    1.48949451885331, -0.787584852115686, -4.934382699854, 29.0731805864111, 
    -2.26200238484375, 4.65925660604302, 4.57357539667069, 13.5774688780233, 
    -7.43056606661547, 6.80825163894218, 26.2460480670466, -0.0345819873156576, 
    -4.12627881544668, 21.9890241216193, 8.85020652256215, -4.58203685844702, 
    -1.56753295765628, 6.87606203426416, -1.24701222724131, -5.49773520072737, 
    26.6408805552948, 13.7954350138116, 2.38997658321286), z_diff_LC = c(13.3437666668954, 
    14.5236741281306, 10.7951593816903, 4.84956568132256, 7.45825970577198, 
    21.9209205048645, 13.771397911861, 7.45865297041878, 6.46080539304303, 
    5.14672039650974, 12.5316920559886, 15.2040992604187, 12.6541200645773, 
    14.2950716064143, 10.5446098231127, 6.43989960683895, 16.4096578863693, 
    16.4101967481371, 16.0975590010918, 12.6720845665324, 16.1643139814777, 
    11.6413490880193, 2.83465891620418, 10.8460318787892, 9.15035156783542, 
    10.2708678061698, 14.1911274394713, 23.0683580892434, 16.8380931420443, 
    4.8403754007098, 7.18799162588475, 6.36638381655323, 8.24158256116018, 
    11.3007628036994, 12.9255831702492, 6.41222412825569, 19.7883919842208, 
    13.3191292882506, 12.7806778770094, 4.86388566858485, 14.6793005237244, 
    2.42776728708029, 7.3976730645803, 12.0699413784232, 6.69843620821456, 
    12.048529261754, -0.949761782343618, 24.7048534238846, 7.06724785291648, 
    1.66908179491139, -0.863601498137782, 11.8756265308355, 11.5238370520726, 
    4.17572476604349, 10.6038524757556, 11.5103217175066, 11.4243857521004, 
    1.35708802651482, 1.5516675954511, 13.6221661122224), cross_effect = c(389.90255733412, 
    286.309185320327, 350.112703646141, 196.068687824073, 210.618189023313, 
    184.100589962345, 268.500499071992, 182.679710049712, 145.851303388469, 
    242.888924115937, 290.331765504451, 223.495952565212, 368.378972611168, 
    342.885214819243, 159.184238145282, 255.455759056413, 228.162929457284, 
    258.430636780864, 339.004872283188, 242.244981818045, 279.955996695361, 
    234.44683308484, 160.422067909279, 452.25181006546, 164.817030867431, 
    151.071088894453, 191.841094098312, 211.677575913499, 237.18132907835, 
    195.00309824532, 211.160343502993, 157.422248048499, 166.692037144187, 
    154.708060297142, 409.919866908005, 144.720624814428, 219.212757331124, 
    200.574858840204, 146.614881240112, 147.858078792705, 151.376676691316, 
    147.495984893396, 153.57867248235, 170.346310895203, 176.052419743554, 
    450.435087632251, 126.7843049186, 165.857455053767, 174.519614000254, 
    114.88606242825, 162.583693543054, 191.307321367729, 180.668616024358, 
    120.84384072861, 129.406507396634, 142.733211798408, 481.353346449074, 
    108.452084188371, 126.939584494314, 212.473450629856)), row.names = c(NA, 
-60L), key = structure(list(rowname = c("1", "10", "100", "101", 
"102", "103", "104", "105", "106", "107", "108", "109", "11", 
"110", "111", "112", "113", "114", "115", "116", "117", "118", 
"119", "12", "120", "121", "122", "123", "124", "125", "126", 
"127", "128", "129", "13", "130", "131", "132", "133", "134", 
"135", "136", "137", "138", "139", "14", "140", "141", "142", 
"143", "144", "145", "146", "147", "148", "149", "15", "150", 
"151", "152"), .rows = structure(list(1L, 2L, 3L, 4L, 5L, 6L, 
    7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 
    19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 
    31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 
    43L, 44L, 45L, 46L, 47L, 48L, 49L, 50L, 51L, 52L, 53L, 54L, 
    55L, 56L, 57L, 58L, 59L, 60L), ptype = integer(0), class = c("vctrs_list_of", 
"vctrs_vctr", "list"))), row.names = c(NA, 60L), class = c("tbl_df", 
"tbl", "data.frame"), .drop = TRUE), index = structure("day", ordered = TRUE), index2 = "day", interval = structure(list(
    year = 0, quarter = 0, month = 0, week = 0, day = 0, hour = 1, 
    minute = 0, second = 0, millisecond = 0, microsecond = 0, 
    nanosecond = 0, unit = 0), .regular = TRUE, class = c("interval", 
"vctrs_rcrd", "vctrs_vctr")), class = c("tbl_ts", "tbl_df", "tbl", 
"data.frame"))

我的_中断%
变异（交叉效应gp=as.factor（如果其他（交叉效应>销售，“提升”、“下降”）））%>%
ggplot（不良事件（x=天，组=项目））+
geom_ribbon（aes（ymin=销售额，ymax=交叉效应，fill=销售额-交叉效应>0），fill=“蓝色粉末”）+
几何线条（aes（y=销售额，颜色=互动（项目，交叉效果），尺寸=0.25）+
几何图形线（aes（y=交叉效应），尺寸=0.25，线型=“twodash”，颜色=“#F8766D”）+
面_包裹（~项目，刻度='自由'，nrow=2）+
缩放y连续（打断=我的打断，标签=我的标签）+
比例填充手册（值=c（“绿松石4”、“绿色1”、“绿松石4”、“深绿色”））
结构(列表)日期=结构(c)(15463080015470784001554850800,，
1554937200, 1555023600, 1555110000, 1555196400, 1555282800, 1555369200, 
1555455600, 1555542000, 1555628400, 1547164800, 1555714800, 1555801200, 
1555887600, 1555974000, 1556060400, 1556146800, 1556233200, 1556319600, 
1556406000, 1556492400, 1547251200, 1556578800, 1556665200, 1556751600, 
1556838000, 1556924400, 1557010800, 1557097200, 1557183600, 1557270000, 
1557356400, 1547337600, 1557442800, 1557529200, 1557615600, 1557702000, 
1557788400, 1557874800, 1557961200, 1558047600, 1558134000, 1558220400, 
1547424000, 1558306800, 1558393200, 1558479600, 1558566000, 1558652400, 
1558738800, 1558825200, 1558911600, 1558998000, 1559084400, 1547510400, 
155917080015592572001559343600），tzone=“”，class=c（“POSIXct”，
“POSIXt”）），rowname=c（“1”、“10”、“100”、“101”、“102”、“103”，
"104", "105", "106", "107", "108", "109", "11", "110", "111", 
"112", "113", "114", "115", "116", "117", "118", "119", "12", 
"120", "121", "122", "123", "124", "125", "126", "127", "128", 
"129", "13", "130", "131", "132", "133", "134", "135", "136", 
"137", "138", "139", "14", "140", "141", "142", "143", "144", 
"145", "146", "147", "148", "149", "15", "150", "151", "152"), 
项目=结构（c）（1L、1L、1L、1L、1L、1L、1L、1L、1L、1L、1L、，
1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，
1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，
1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，
1L，1L，1L，1L，1L，1L），标签=c（“项目A”，“项目B”），类别=“系数”），
销售=c（344L，250L，316L，187L，196L，151L，236L，170L，
137L、231L、258L、194L、327L、300L、144L、240L、196L、222L、，
292L、215L、241L、210L、156L、408L、151L、137L、168L、172L、，
203L、186L、197L、148L、154L、139L、363L、136L、183L、177L、，
130L、141L、132L、144L、143L、152L、165L、402L、128L、133L、，
163L、113L、164L、171L、162L、116L、117L、128L、432L、107L、，
（15.5644333787362，1.87906641317019，
12.557755209854, 14.8812985333839, 17.5223825569917, 23.8360074736518, 
18.7410953048883, 14.9583507793006, 13.9273511861036, -3.51818494122973, 
12.1544583602306, 3.02440323681235, 3.82962965039171, 17.5478815812969, 
3.3229377520704, 0.633981373873377, 9.27905096386199, 12.5799626114306, 
14.2247591638052, 16.6487747981391, 15.8304549924645, 9.15979751528926, 
15.0129291111416, -0.688334784614703, -7.63226366995004, 
0.428951331549642, 10.2702773598704, 36.1219319585148, 15.4142833246758, 
4.88470834307489, 21.2490429809954, -7.33361550396995, -4.29869918645501, 
18.9489364038734, -1.76460720804452, -1.35823311958288, 34.6935883900468, 
1.48949451885331, -0.787584852115686, -4.934382699854, 29.0731805864111, 
-2.26200238484375, 4.65925660604302, 4.57357539667069, 13.5774688780233, 
-7.43056606661547, 6.80825163894218, 26.2460480670466, -0.0345819873156576, 
-4.12627881544668, 21.9890241216193, 8.85020652256215, -4.58203685844702, 
-1.56753295765628, 6.87606203426416, -1.24701222724131, -5.49773520072737, 
26.640880552948，13.7954350138116，2.38997658321286），z_diff_LC=c（13.3437666668954，
14.5236741281306, 10.7951593816903, 4.84956568132256, 7.45825970577198, 
21.9209205048645, 13.771397911861, 7.45865297041878, 6.46080539304303, 
5.14672039650974, 12.5316920559886, 15.2040992604187, 12.6541200645773, 
14.2950716064143, 10.5446098231127, 6.43989960683895, 16.4096578863693, 
16.4101967481371, 16.0975590010918, 12.6720845665324, 16.1643139814777, 
11.6413490880193, 2.83465891620418, 10.8460318787892, 9.15035156783542, 
10.2708678061698, 14.1911274394713, 23.0683580892434, 16.8380931420443, 
4.8403754007098, 7.18799162588475, 6.36638381655323, 8.24158256116018, 
11.3007628036994, 12.9255831702492, 6.41222412825569, 19.7883919842208, 
13.3191292882506, 12.7806778770094, 4.86388566858485, 14.6793005237244, 
2.42776728708029, 7.3976730645803, 12.0699413784232, 6.69843620821456, 
12.048529261754, -0.94976178234