Plotting years over same x-axis in months - Reprex

tidyverse
,
1

Hi,

I have a dataset which I am trying to plot Revenue by year over the 12 month period of each year.

After exploring the data and decided to generate a simple Revenue X Time simple plot.

My issue is that when I group by year, I lose the "roughness" / "jaggedness" of the daily variations as well as the x-axis comes out of format. Any insight on what might be the issue here and how to get the plot to have x-axis Jan-Dez grouped by year.

Please find my below reprex:

library(tidyverse)
library(lubridate)

# Fictitious sample data of total revenue or amount billed by date.
x <- tribble(
~ActualInvDate,	~Tot.Billed.Amt,

"2-20-2018",	2315,
"2-22-2018", 	825,
"2-23-2018", 	710,
"2-26-2018", 	1032,
"2-27-2018", 	2519,
"3-1-2018", 	5709,
"3-6-2018", 	3457,
"3-9-2018", 	2380,
"3-19-2018", 	2515,
"3-23-2018", 	1399,
"3-26-2018", 	915,
"3-28-2018", 	2846,
"4-3-2018", 	2995,
"4-6-2018", 	1848,
"4-16-2018", 	2163,
"4-17-2018", 	3316,
"4-18-2018", 	4051,
"4-19-2018", 	9872,
"4-20-2018", 	3258,
"4-23-2018", 	3248,
"4-24-2018", 	2609,
"4-25-2018", 	3436,
"4-26-2018", 	1128,
"4-27-2018", 	7194,
"4-30-2018", 	1725,
"5-1-2018", 	8568,
"5-2-2018", 	5845,
"5-3-2018", 	8665,
"5-4-2018", 	12012,
"5-7-2018", 	6676,
"5-8-2018", 	12266,
"5-9-2018", 	20535,
"5-10-2018", 	15335,
"5-11-2018", 	65970,
"5-14-2018", 	2230,
"5-15-2018", 	7316,
"5-16-2018", 	8852,
"5-17-2018", 	63012,
"5-18-2018", 	34252,
"5-21-2018", 	7421,
"5-22-2018", 	6600,
"5-23-2018", 	19201,
"5-24-2018", 	11100,
"5-25-2018", 	50899,
"5-26-2018", 	3800,
"5-29-2018", 	13308,
"5-30-2018", 	7512,
"5-31-2018", 	22619,
"6-1-2018", 	39321,
"6-4-2018", 	3566,
"6-5-2018", 	13047,
"6-6-2018", 	138839,
"6-7-2018", 	26474,
"6-8-2018", 	29660,
"6-11-2018", 	8637,
"6-12-2018", 	22942,
"6-13-2018", 	30953,
"6-14-2018", 	126284,
"6-15-2018", 	55290,
"6-18-2018", 	9670,
"6-19-2018", 	42982,
"6-20-2018", 	88784,
"6-21-2018", 	41224,
"6-22-2018", 	16450,
"6-25-2018", 	26242,
"6-26-2018", 	256503,
"6-27-2018", 	18127,
"6-28-2018", 	27626,
"6-29-2018", 	45475,
"7-2-2018", 	53976,
"7-3-2018", 	25175,
"7-5-2018", 	37834,
"7-6-2018", 	33602,
"7-9-2018", 	79154,
"7-10-2018", 	16275,
"7-11-2018", 	105632,
"7-12-2018", 	22028,
"7-13-2018", 	22039,
"7-16-2018", 	63600,
"7-17-2018", 	12807,
"7-18-2018", 	28392,
"7-19-2018", 	24746,
"7-20-2018", 	44127,
"7-23-2018", 	18321,
"7-24-2018", 	58024,
"7-25-2018", 	17775,
"7-26-2018", 	29174,
"7-27-2018", 	35527,
"7-30-2018", 	52932,
"7-31-2018", 	17608,
"8-1-2018", 	73385,
"8-2-2018", 	31679,
"8-3-2018", 	53366,
"8-6-2018", 	107639,
"8-7-2018", 	10754,
"8-8-2018", 	36492,
"8-9-2018", 	78571,
"8-10-2018", 	43583,
"8-13-2018", 	30338,
"8-14-2018", 	38666,
"8-15-2018", 	46697,
"8-16-2018", 	68630,
"8-17-2018", 	58900,
"8-20-2018", 	33593,
"8-21-2018", 	33823,
"8-22-2018", 	25898,
"8-23-2018", 	21140,
"8-24-2018", 	26173,
"8-27-2018", 	57885,
"8-28-2018", 	27521,
"8-29-2018", 	93063,
"8-30-2018", 	40859,
"8-31-2018", 	14984,
"9-4-2018", 	53205,
"9-5-2018", 	84689,
"9-6-2018", 	51083,
"9-7-2018", 	64887,
"9-10-2018", 	16876,
"9-11-2018", 	34002,
"9-12-2018", 	75343,
"9-13-2018", 	35299,
"9-14-2018", 	24313,
"9-16-2018", 	12994,
"9-17-2018", 	23038,
"9-18-2018", 	69125,
"9-19-2018", 	115924,
"9-20-2018", 	77321,
"9-21-2018", 	71522,
"9-24-2018", 	54669,
"9-25-2018", 	166560,
"9-26-2018", 	32937,
"9-27-2018", 	45888,
"9-28-2018", 	55788,
"10-1-2018", 	76223,
"10-2-2018", 	38322,
"10-3-2018", 	131780,
"10-4-2018", 	24949,
"10-5-2018", 	72824,
"10-8-2018", 	32683,
"10-9-2018", 	11963,
"10-10-2018", 	48699,
"10-11-2018", 	21639,
"10-12-2018", 	67049,
"10-15-2018", 	29531,
"10-16-2018", 	33038,
"10-17-2018", 	27702,
"10-18-2018", 	108123,
"10-19-2018", 	37491,
"10-22-2018", 	42021,
"10-23-2018", 	436226,
"10-24-2018", 	85408,
"10-25-2018", 	48811,
"10-26-2018", 	48260,
"10-29-2018", 	115547,
"10-30-2018", 	87492,
"10-31-2018", 	102753,
"11-1-2018", 	40049,
"11-2-2018", 	99763,
"11-3-2018", 	1583,
"11-5-2018", 	31273,
"11-6-2018", 	32896,
"11-7-2018", 	44155,
"11-8-2018", 	50792,
"11-9-2018", 	35316,
"11-12-2018", 	13245,
"11-13-2018", 	36688,
"11-14-2018", 	58860,
"11-15-2018", 	120772,
"11-16-2018", 	72833,
"11-19-2018", 	65900,
"11-20-2018", 	57201,
"11-21-2018", 	89682,
"11-23-2018", 	25196,
"11-26-2018", 	26029,
"11-27-2018", 	177255,
"11-28-2018", 	192322,
"11-29-2018", 	90096,
"11-30-2018", 	40402,
"12-3-2018", 	41149,
"12-4-2018", 	36235,
"12-5-2018", 	193966,
"12-6-2018", 	140907,
"12-7-2018", 	335491,
"12-10-2018", 	26606,
"12-11-2018", 	52543,
"12-12-2018", 	71969,
"12-13-2018", 	42853,
"12-14-2018", 	194443,
"12-17-2018", 	31843,
"12-18-2018", 	37400,
"12-19-2018", 	68673,
"12-20-2018", 	96150,
"12-21-2018", 	106817,
"12-24-2018", 	9951,
"12-26-2018", 	47133,
"12-27-2018", 	53725,
"12-28-2018", 	91384,
"12-31-2018", 	46223,
"1-2-2019", 	134153,
"1-3-2019", 	25835,
"1-4-2019", 	105737,
"1-7-2019", 	117669,
"1-8-2019", 	64041,
"1-9-2019", 	56282,
"1-10-2019", 	57692,
"1-11-2019", 	62629,
"1-14-2019", 	19359,
"1-15-2019", 	90822,
"1-16-2019", 	105597,
"1-17-2019", 	109124,
"1-18-2019", 	67683,
"1-21-2019", 	138530,
"1-22-2019", 	111611,
"1-23-2019", 	129246,
"1-24-2019", 	73279,
"1-25-2019", 	87689,
"1-28-2019", 	35619,
"1-29-2019", 	23879,
"1-30-2019", 	74315,
"1-31-2019", 	93815,
"2-1-2019", 	20004,
"2-4-2019", 	39538,
"2-5-2019", 	21436,
"2-6-2019", 	50803,
"2-7-2019", 	53845,
"2-8-2019", 	91022,
"2-11-2019", 	60783,
"2-12-2019", 	54061,
"2-13-2019", 	115675,
"2-14-2019", 	26104,
"2-15-2019", 	172181,
"2-18-2019", 	103545,
"2-19-2019", 	56036,
"2-20-2019", 	102366,
"2-21-2019", 	105714,
"2-22-2019", 	128733,
"2-24-2019", 	4915,
"2-25-2019", 	46749,
"2-26-2019", 	76465,
"2-27-2019", 	73043,
"2-28-2019", 	65527,
"3-1-2019", 	76577,
"3-2-2019", 	1275,
"3-3-2019", 	1056,
"3-4-2019", 	84193,
"3-5-2019", 	39162,
"3-6-2019", 	45854,
"3-7-2019", 	52611,
"3-8-2019", 	202706,
"3-9-2019", 	1574,
"3-11-2019", 	191915,
"3-12-2019", 	66025,
"3-13-2019", 	50385,
"3-14-2019", 	104651,
"3-15-2019", 	178230,
"3-16-2019", 	1819,
"3-18-2019", 	176311,
"3-19-2019", 	113162,
"3-20-2019", 	193697,
"3-21-2019", 	236478,
"3-22-2019", 	137631,
"3-24-2019", 	4494,
"3-25-2019", 	172074,
"3-26-2019", 	286207,
"3-27-2019", 	134305,
"3-28-2019", 	158184,
"3-29-2019", 	82140,
"4-1-2019", 	113498,
"4-2-2019", 	180771,
"4-3-2019", 	80910,
"4-4-2019", 	81043,
"4-5-2019", 	79580,
"4-6-2019", 	1249,
"4-7-2019", 	25047,
"4-8-2019", 	112628,
"4-9-2019", 	92044,
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"4-22-2019", 	83021,
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"4-24-2019", 	77150,
"4-25-2019", 	84455,
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"4-29-2019", 	76470,
"4-30-2019", 	140846,
"5-1-2019", 	127323,
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"8-1-2019", 	118792,
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"8-20-2019", 	312579,
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"8-23-2019", 	155308,
"8-26-2019", 	324124,
"8-27-2019", 	293942,
"8-28-2019", 	183753,
"8-29-2019", 	217908,
"8-30-2019", 	81776,
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"4-6-2020", 	133797,
"4-7-2020", 	140002,
"4-8-2020", 	385024,
"4-9-2020", 	151364,
"4-10-2020", 	70551,
"4-12-2020", 	3814,
"4-13-2020", 	331806,
"4-14-2020", 	300080,
"4-15-2020", 	223719,
"4-16-2020", 	235440,
"4-17-2020", 	42567,
"4-20-2020", 	154566,
"4-21-2020", 	323098,
"4-22-2020", 	39385,
"4-23-2020", 	298896,
"4-24-2020", 	234195,
"4-27-2020", 	177914,
"4-28-2020", 	441017,
"4-29-2020", 	223406,
"4-30-2020", 	278052,
"5-1-2020", 	226830,
"5-3-2020", 	1898,
"5-4-2020", 	314639,
"5-5-2020", 	228052,
"5-6-2020", 	110759,
"5-7-2020", 	204911,
"5-8-2020", 	239334,
"5-10-2020", 	2020,
"5-11-2020", 	167912,
"5-12-2020", 	250557,
"5-13-2020", 	161858,
"5-14-2020", 	277749,
"5-15-2020", 	117101,
"5-17-2020", 	3864,
"5-18-2020", 	192543,
"5-19-2020", 	274125,
"5-20-2020", 	162523,
"5-21-2020", 	147519,
"5-22-2020", 	157107,
"5-26-2020", 	349935,
"5-27-2020", 	58701,
"5-28-2020", 	182074,
"5-29-2020", 	355316,
"5-30-2020", 	1570,
"5-31-2020", 	19866,
"6-1-2020", 	488207,
"6-2-2020", 	207082,
"6-3-2020", 	286356,
"6-4-2020", 	280647,
"6-5-2020", 	208814,
"6-8-2020", 	257497,
"6-9-2020", 	171638,
"6-10-2020", 	142506,
"6-11-2020", 	181565,
"6-12-2020", 	136672,
"6-13-2020", 	29165,
"6-15-2020", 	607336,
"6-16-2020", 	389575,
"6-17-2020", 	183919,
"6-18-2020", 	295681,
"6-19-2020", 	199838,
"6-22-2020", 	380438,
"6-23-2020", 	121738,
"6-24-2020", 	101299,
"6-25-2020", 	216002,
"6-26-2020", 	137952,
"6-27-2020", 	107081,
"6-29-2020", 	336415,
"6-30-2020", 	396493,
"7-1-2020", 	179598,
"7-2-2020", 	95814,
"7-3-2020", 	20702,
"7-6-2020", 	285842,
"7-7-2020", 	232135,
"7-8-2020", 	215388,
"7-9-2020", 	153461,
"7-10-2020", 	176932,
"7-13-2020", 	208367)

# Breaking into y/m/d and rename it:
x <- x %>% mutate(`ActualInvDate` = mdy(`ActualInvDate`)) %>% 
  mutate_at(vars(`ActualInvDate`),
                funs(year, month, day)) %>%
  rename("Act.Inv.Year" = `year`,
         "Act.Inv.Month" = `month`,
         "Act.Inv.Day" = `day`
  ) %>% mutate(`Act.Inv.Year` = as.factor(`Act.Inv.Year`)) # Ensure Factor for plotting by year
               

#Plot 1
# Simple revenue x time 
ggplot(data = x,
       aes(
         x = `ActualInvDate`, y = `Tot.Billed.Amt`/1000
       )) + geom_line()


# Plot2
# grouped by year, issue on x-axis (should be the months),
# lost the "granularity" of first 
ggplot(data = x,
       aes(x = `Act.Inv.Month`, y = `Tot.Billed.Amt`/1000,
           color = `Act.Inv.Year`
       )) + 
  geom_line() +   
  labs(x = "Invoice Date", y = "Amount Billed (Thousands $)")

Any feedback would be much appreciated.

Thanks.

2

I think this gets you close to what you want.

x <- x %>% mutate(`ActualInvDate` = mdy(`ActualInvDate`)) %>% 
  mutate_at(vars(`ActualInvDate`),
            funs(year, month, day)) %>%
  rename("Act.Inv.Year" = `year`,
         "Act.Inv.Month" = `month`,
         "Act.Inv.Day" = `day`
  ) %>% mutate(`Act.Inv.Year` = as.factor(`Act.Inv.Year`)) # Ensure Factor for plotting by year

x <- mutate(x, DayofYear = yday(ActualInvDate))

ggplot(x, aes(DayofYear, Tot.Billed.Amt/1000, color = Act.Inv.Year)) + geom_line()

I am not sure how you would want to label the x axis due to 2020 being a leap year. March 1 is the 60th day of the in 2018 and 2019 but it is the 61st in 2020. I would leave the axis as Day of Year but the choice is yours.

3

Not sure what you're after

library(tidyverse)
library(lubridate)
#> 
#> Attaching package: 'lubridate'
#> The following objects are masked from 'package:base':
#> 
#>     date, intersect, setdiff, union

# Fictitious sample data of total revenue or amount billed by date.
x <- tribble(
    ~ActualInvDate, ~Tot.Billed.Amt,
    
    "2-20-2018",    2315,
    "2-22-2018",    825,
    "2-23-2018",    710,
    "2-26-2018",    1032,
    "2-27-2018",    2519,
    "3-1-2018",     5709,
    "3-6-2018",     3457,
    "3-9-2018",     2380,
    "3-19-2018",    2515,
    "3-23-2018",    1399,
    "3-26-2018",    915,
    "3-28-2018",    2846,
    "4-3-2018",     2995,
    "4-6-2018",     1848,
    "4-16-2018",    2163,
    "4-17-2018",    3316,
    "4-18-2018",    4051,
    "4-19-2018",    9872,
    "4-20-2018",    3258,
    "4-23-2018",    3248,
    "4-24-2018",    2609,
    "4-25-2018",    3436,
    "4-26-2018",    1128,
    "4-27-2018",    7194,
    "4-30-2018",    1725,
    "5-1-2018",     8568,
    "5-2-2018",     5845,
    "5-3-2018",     8665,
    "5-4-2018",     12012,
    "5-7-2018",     6676,
    "5-8-2018",     12266,
    "5-9-2018",     20535,
    "5-10-2018",    15335,
    "5-11-2018",    65970,
    "5-14-2018",    2230,
    "5-15-2018",    7316,
    "5-16-2018",    8852,
    "5-17-2018",    63012,
    "5-18-2018",    34252,
    "5-21-2018",    7421,
    "5-22-2018",    6600,
    "5-23-2018",    19201,
    "5-24-2018",    11100,
    "5-25-2018",    50899,
    "5-26-2018",    3800,
    "5-29-2018",    13308,
    "5-30-2018",    7512,
    "5-31-2018",    22619,
    "6-1-2018",     39321,
    "6-4-2018",     3566,
    "6-5-2018",     13047,
    "6-6-2018",     138839,
    "6-7-2018",     26474,
    "6-8-2018",     29660,
    "6-11-2018",    8637,
    "6-12-2018",    22942,
    "6-13-2018",    30953,
    "6-14-2018",    126284,
    "6-15-2018",    55290,
    "6-18-2018",    9670,
    "6-19-2018",    42982,
    "6-20-2018",    88784,
    "6-21-2018",    41224,
    "6-22-2018",    16450,
    "6-25-2018",    26242,
    "6-26-2018",    256503,
    "6-27-2018",    18127,
    "6-28-2018",    27626,
    "6-29-2018",    45475,
    "7-2-2018",     53976,
    "7-3-2018",     25175,
    "7-5-2018",     37834,
    "7-6-2018",     33602,
    "7-9-2018",     79154,
    "7-10-2018",    16275,
    "7-11-2018",    105632,
    "7-12-2018",    22028,
    "7-13-2018",    22039,
    "7-16-2018",    63600,
    "7-17-2018",    12807,
    "7-18-2018",    28392,
    "7-19-2018",    24746,
    "7-20-2018",    44127,
    "7-23-2018",    18321,
    "7-24-2018",    58024,
    "7-25-2018",    17775,
    "7-26-2018",    29174,
    "7-27-2018",    35527,
    "7-30-2018",    52932,
    "7-31-2018",    17608,
    "8-1-2018",     73385,
    "8-2-2018",     31679,
    "8-3-2018",     53366,
    "8-6-2018",     107639,
    "8-7-2018",     10754,
    "8-8-2018",     36492,
    "8-9-2018",     78571,
    "8-10-2018",    43583,
    "8-13-2018",    30338,
    "8-14-2018",    38666,
    "8-15-2018",    46697,
    "8-16-2018",    68630,
    "8-17-2018",    58900,
    "8-20-2018",    33593,
    "8-21-2018",    33823,
    "8-22-2018",    25898,
    "8-23-2018",    21140,
    "8-24-2018",    26173,
    "8-27-2018",    57885,
    "8-28-2018",    27521,
    "8-29-2018",    93063,
    "8-30-2018",    40859,
    "8-31-2018",    14984,
    "9-4-2018",     53205,
    "9-5-2018",     84689,
    "9-6-2018",     51083,
    "9-7-2018",     64887,
    "9-10-2018",    16876,
    "9-11-2018",    34002,
    "9-12-2018",    75343,
    "9-13-2018",    35299,
    "9-14-2018",    24313,
    "9-16-2018",    12994,
    "9-17-2018",    23038,
    "9-18-2018",    69125,
    "9-19-2018",    115924,
    "9-20-2018",    77321,
    "9-21-2018",    71522,
    "9-24-2018",    54669,
    "9-25-2018",    166560,
    "9-26-2018",    32937,
    "9-27-2018",    45888,
    "9-28-2018",    55788,
    "10-1-2018",    76223,
    "10-2-2018",    38322,
    "10-3-2018",    131780,
    "10-4-2018",    24949,
    "10-5-2018",    72824,
    "10-8-2018",    32683,
    "10-9-2018",    11963,
    "10-10-2018",   48699,
    "10-11-2018",   21639,
    "10-12-2018",   67049,
    "10-15-2018",   29531,
    "10-16-2018",   33038,
    "10-17-2018",   27702,
    "10-18-2018",   108123,
    "10-19-2018",   37491,
    "10-22-2018",   42021,
    "10-23-2018",   436226,
    "10-24-2018",   85408,
    "10-25-2018",   48811,
    "10-26-2018",   48260,
    "10-29-2018",   115547,
    "10-30-2018",   87492,
    "10-31-2018",   102753,
    "11-1-2018",    40049,
    "11-2-2018",    99763,
    "11-3-2018",    1583,
    "11-5-2018",    31273,
    "11-6-2018",    32896,
    "11-7-2018",    44155,
    "11-8-2018",    50792,
    "11-9-2018",    35316,
    "11-12-2018",   13245,
    "11-13-2018",   36688,
    "11-14-2018",   58860,
    "11-15-2018",   120772,
    "11-16-2018",   72833,
    "11-19-2018",   65900,
    "11-20-2018",   57201,
    "11-21-2018",   89682,
    "11-23-2018",   25196,
    "11-26-2018",   26029,
    "11-27-2018",   177255,
    "11-28-2018",   192322,
    "11-29-2018",   90096,
    "11-30-2018",   40402,
    "12-3-2018",    41149,
    "12-4-2018",    36235,
    "12-5-2018",    193966,
    "12-6-2018",    140907,
    "12-7-2018",    335491,
    "12-10-2018",   26606,
    "12-11-2018",   52543,
    "12-12-2018",   71969,
    "12-13-2018",   42853,
    "12-14-2018",   194443,
    "12-17-2018",   31843,
    "12-18-2018",   37400,
    "12-19-2018",   68673,
    "12-20-2018",   96150,
    "12-21-2018",   106817,
    "12-24-2018",   9951,
    "12-26-2018",   47133,
    "12-27-2018",   53725,
    "12-28-2018",   91384,
    "12-31-2018",   46223,
    "1-2-2019",     134153,
    "1-3-2019",     25835,
    "1-4-2019",     105737,
    "1-7-2019",     117669,
    "1-8-2019",     64041,
    "1-9-2019",     56282,
    "1-10-2019",    57692,
    "1-11-2019",    62629,
    "1-14-2019",    19359,
    "1-15-2019",    90822,
    "1-16-2019",    105597,
    "1-17-2019",    109124,
    "1-18-2019",    67683,
    "1-21-2019",    138530,
    "1-22-2019",    111611,
    "1-23-2019",    129246,
    "1-24-2019",    73279,
    "1-25-2019",    87689,
    "1-28-2019",    35619,
    "1-29-2019",    23879,
    "1-30-2019",    74315,
    "1-31-2019",    93815,
    "2-1-2019",     20004,
    "2-4-2019",     39538,
    "2-5-2019",     21436,
    "2-6-2019",     50803,
    "2-7-2019",     53845,
    "2-8-2019",     91022,
    "2-11-2019",    60783,
    "2-12-2019",    54061,
    "2-13-2019",    115675,
    "2-14-2019",    26104,
    "2-15-2019",    172181,
    "2-18-2019",    103545,
    "2-19-2019",    56036,
    "2-20-2019",    102366,
    "2-21-2019",    105714,
    "2-22-2019",    128733,
    "2-24-2019",    4915,
    "2-25-2019",    46749,
    "2-26-2019",    76465,
    "2-27-2019",    73043,
    "2-28-2019",    65527,
    "3-1-2019",     76577,
    "3-2-2019",     1275,
    "3-3-2019",     1056,
    "3-4-2019",     84193,
    "3-5-2019",     39162,
    "3-6-2019",     45854,
    "3-7-2019",     52611,
    "3-8-2019",     202706,
    "3-9-2019",     1574,
    "3-11-2019",    191915,
    "3-12-2019",    66025,
    "3-13-2019",    50385,
    "3-14-2019",    104651,
    "3-15-2019",    178230,
    "3-16-2019",    1819,
    "3-18-2019",    176311,
    "3-19-2019",    113162,
    "3-20-2019",    193697,
    "3-21-2019",    236478,
    "3-22-2019",    137631,
    "3-24-2019",    4494,
    "3-25-2019",    172074,
    "3-26-2019",    286207,
    "3-27-2019",    134305,
    "3-28-2019",    158184,
    "3-29-2019",    82140,
    "4-1-2019",     113498,
    "4-2-2019",     180771,
    "4-3-2019",     80910,
    "4-4-2019",     81043,
    "4-5-2019",     79580,
    "4-6-2019",     1249,
    "4-7-2019",     25047,
    "4-8-2019",     112628,
    "4-9-2019",     92044,
    "4-10-2019",    107552,
    "4-11-2019",    102431,
    "4-12-2019",    83815,
    "4-14-2019",    7185,
    "4-15-2019",    79806,
    "4-16-2019",    221777,
    "4-17-2019",    94871,
    "4-18-2019",    112382,
    "4-19-2019",    58334,
    "4-22-2019",    83021,
    "4-23-2019",    111868,
    "4-24-2019",    77150,
    "4-25-2019",    84455,
    "4-26-2019",    104736,
    "4-29-2019",    76470,
    "4-30-2019",    140846,
    "5-1-2019",     127323,
    "5-2-2019",     139238,
    "5-3-2019",     92862,
    "5-6-2019",     283460,
    "5-7-2019",     127881,
    "5-8-2019",     79966,
    "5-9-2019",     159864,
    "5-10-2019",    87209,
    "5-13-2019",    107573,
    "5-14-2019",    171410,
    "5-15-2019",    108894,
    "5-16-2019",    89317,
    "5-17-2019",    74481,
    "5-20-2019",    148184,
    "5-21-2019",    215174,
    "5-22-2019",    51308,
    "5-23-2019",    110106,
    "5-24-2019",    92743,
    "5-26-2019",    29351,
    "5-27-2019",    18849,
    "5-28-2019",    240982,
    "5-29-2019",    134842,
    "5-30-2019",    106541,
    "5-31-2019",    99460,
    "6-2-2019",     8412,
    "6-3-2019",     118405,
    "6-4-2019",     144759,
    "6-5-2019",     123294,
    "6-6-2019",     67532,
    "6-7-2019",     202912,
    "6-10-2019",    164081,
    "6-11-2019",    367452,
    "6-12-2019",    189177,
    "6-13-2019",    90003,
    "6-14-2019",    119539,
    "6-17-2019",    169452,
    "6-18-2019",    196062,
    "6-19-2019",    104542,
    "6-20-2019",    62737,
    "6-21-2019",    75287,
    "6-24-2019",    127385,
    "6-25-2019",    295774,
    "6-26-2019",    279868,
    "6-27-2019",    100558,
    "6-28-2019",    78487,
    "7-1-2019",     127187,
    "7-2-2019",     285203,
    "7-3-2019",     48705,
    "7-5-2019",     115280,
    "7-7-2019",     1207,
    "7-8-2019",     124428,
    "7-9-2019",     251938,
    "7-10-2019",    104617,
    "7-11-2019",    141377,
    "7-12-2019",    187875,
    "7-15-2019",    117554,
    "7-16-2019",    212808,
    "7-17-2019",    147232,
    "7-18-2019",    149241,
    "7-19-2019",    94922,
    "7-22-2019",    209061,
    "7-23-2019",    192436,
    "7-24-2019",    258726,
    "7-25-2019",    272500,
    "7-26-2019",    183545,
    "7-28-2019",    3450,
    "7-29-2019",    150473,
    "7-30-2019",    322693,
    "7-31-2019",    154438,
    "8-1-2019",     118792,
    "8-2-2019",     127683,
    "8-5-2019",     193117,
    "8-6-2019",     258290,
    "8-7-2019",     149324,
    "8-8-2019",     134461,
    "8-9-2019",     58165,
    "8-10-2019",    1728,
    "8-12-2019",    100383,
    "8-13-2019",    204296,
    "8-14-2019",    107806,
    "8-15-2019",    198694,
    "8-16-2019",    203261,
    "8-19-2019",    186531,
    "8-20-2019",    312579,
    "8-21-2019",    99326,
    "8-22-2019",    190502,
    "8-23-2019",    155308,
    "8-26-2019",    324124,
    "8-27-2019",    293942,
    "8-28-2019",    183753,
    "8-29-2019",    217908,
    "8-30-2019",    81776,
    "8-31-2019",    11544,
    "9-3-2019",     191848,
    "9-4-2019",     315857,
    "9-5-2019",     231207,
    "9-6-2019",     125868,
    "9-7-2019",     2337,
    "9-9-2019",     146405,
    "9-10-2019",    252506,
    "9-11-2019",    124663,
    "9-12-2019",    198406,
    "9-13-2019",    137195,
    "9-14-2019",    972,
    "9-16-2019",    124401,
    "9-17-2019",    246132,
    "9-18-2019",    127232,
    "9-19-2019",    216183,
    "9-20-2019",    177872,
    "9-22-2019",    2755,
    "9-23-2019",    232763,
    "9-24-2019",    257909,
    "9-25-2019",    169977,
    "9-26-2019",    205241,
    "9-27-2019",    144566,
    "9-30-2019",    269271,
    "10-1-2019",    208830,
    "10-2-2019",    159483,
    "10-3-2019",    213372,
    "10-4-2019",    148954,
    "10-5-2019",    514,
    "10-7-2019",    146648,
    "10-8-2019",    299011,
    "10-9-2019",    254048,
    "10-10-2019",   256041,
    "10-11-2019",   119752,
    "10-14-2019",   115786,
    "10-15-2019",   180412,
    "10-16-2019",   305405,
    "10-17-2019",   106641,
    "10-18-2019",   105346,
    "10-20-2019",   3150,
    "10-21-2019",   240890,
    "10-22-2019",   317188,
    "10-23-2019",   189734,
    "10-24-2019",   77177,
    "10-25-2019",   165337,
    "10-28-2019",   180917,
    "10-29-2019",   78138,
    "10-30-2019",   176064,
    "10-31-2019",   108147,
    "11-1-2019",    107501,
    "11-2-2019",    2467,
    "11-3-2019",    894,
    "11-4-2019",    217879,
    "11-5-2019",    179882,
    "11-6-2019",    52904,
    "11-7-2019",    119438,
    "11-8-2019",    167452,
    "11-9-2019",    504,
    "11-10-2019",   4232,
    "11-11-2019",   231509,
    "11-12-2019",   214653,
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# Breaking into y/m/d and rename it:
x <- x %>% mutate(`ActualInvDate` = mdy(`ActualInvDate`)) %>% 
    mutate_at(vars(`ActualInvDate`),
              funs(year, month, day)) %>%
    rename("Act.Inv.Year" = `year`,
           "Act.Inv.Month" = `month`,
           "Act.Inv.Day" = `day`
    ) %>% mutate(`Act.Inv.Year` = as.factor(`Act.Inv.Year`)) # Ensure Factor for plotting by year
#> Warning: `funs()` is deprecated as of dplyr 0.8.0.
#> Please use a list of either functions or lambdas: 
#> 
#>   # Simple named list: 
#>   list(mean = mean, median = median)
#> 
#>   # Auto named with `tibble::lst()`: 
#>   tibble::lst(mean, median)
#> 
#>   # Using lambdas
#>   list(~ mean(., trim = .2), ~ median(., na.rm = TRUE))
#> This warning is displayed once every 8 hours.
#> Call `lifecycle::last_warnings()` to see where this warning was generated.


#Plot 1
# Simple revenue x time 
ggplot(data = x,
       aes(
           x = `ActualInvDate`, y = `Tot.Billed.Amt`/1000
       )) + geom_line()




# Plot2
# grouped by year, issue on x-axis (should be the months),
# lost the "granularity" of first 
ggplot(data = x,
       aes(x = ActualInvDate, y = Tot.Billed.Amt/1000,
           color = Act.Inv.Year
       )) + 
    geom_line() +   
    labs(x = "Invoice Date", y = "Amount Billed (Thousands $)") +
    theme_minimal()

Created on 2020-08-04 by the reprex package (v0.3.0)

4

Thank you for you reply!

You got the right idea and I understand you point regarding leap years etc, do you think maybe is it possible to have it by months instead of days then? I'm open to better ways to visualize this information over time.

5

Sorry if I weren't clear, FJCC got the idea but his solution has the x-axis in days of the year.

Basically x-axis being from Jan through Dec and the colored line plots for each year.

ggplot(data = x,
       aes(x = `Act.Inv.Month`, y = `Tot.Billed.Amt`/1000,
           color = `Act.Inv.Year`
       )) + 
  geom_line() +   
  labs(x = "Invoice Date", y = "Amount Billed (Thousands $)")

Looks like:

reprex_revenue
reprex_revenue1212×428 6.87 KB

I'm open for suggestions on better ways to visualize this data. Basically total revenue month by month, each year a different color.

Thanks for your time!

6

minor tweak to fjcc :


x <- mutate(x, week_of_year = week(ActualInvDate))

ggplot(x, aes(week_of_year, 
              Tot.Billed.Amt/1000, 
              color = Act.Inv.Year)) + geom_point(size=.5) +
  geom_smooth() +
  scale_x_continuous(breaks = 0:17*3+1)

image
image852×708 52.6 KB

1 Like
7

@nirgrahamuk very nice! This is actually awesome!

Do you mind explaning a little how you came up with the numbers 0:17*3+1 for:

  scale_x_continuous(breaks = 0:17*3+1)

I see that it is where you want the breaks and how they create a vector from 0 to 52.

>  0:17*3
 [1]  0  3  6  9 12 15 18 21 24 27 30 33 36 39 42 45 48 51
> 0:17*3+1
 [1]  1  4  7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52

Just never seen this and maybe there is some underlying fundamental principal which I'm unaware. Like I get what you did, but never seen or would have thought of managing the breaks like that.

Thanks for that!

8

I want to control the breaks, and I want the first to be 1 and the last to be 52.
I conceptualise it as 0 to 51 (all plus 1), If I used seq() with length, it wont respect my desire to have integers, so some factorisation will be required.
Here is a convenient tool

1,3,17,51
(in practice I didnt use the above but rather a very simple and fast 'trial and error' where I saw that 51 could be divided by 3 17 times. Therefore I was able to generate a sequence with the properties I wanted.

2 Likes
9

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