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11/12/25 8:39:07 PM
Filters
YearQuarterDiff from Monthly Avg
2015Q1-138255
Q2-114072
Q3118
Q472106
2016Q1-149447
Q2-108901
Q3-26631
Q477443
2017Q1-100676
Q2-14986
Q3424
Q4185047
2018Q1-40860
Q2-19621
Q3105354
Q4272958
YearQuarterSalesProfit
2015Q174447.7963811.229
Q286538.759611204.0692
Q3143633.212312804.7218
Q4179627.730221723.9541
2016Q168851.73869264.9416
Q289124.18712190.9224
Q3130259.575216853.6194
Q4182297.008223309.1203
2017Q193237.18111441.3708
Q2136082.30116390.3394
Q3143787.362215823.6048
Q4236098.753838139.8593
2018Q1123144.860223506.2026
Q2133764.37215499.2085
Q3196251.95626985.1325
Q4280054.06727448.726
YearQuarterSales
2015Q174447.796
Q286538.7596
Q3143633.2123
Q4179627.7302
2016Q168851.7386
Q289124.187
Q3130259.5752
Q4182297.0082
2017Q193237.181
Q2136082.301
Q3143787.3622
Q4236098.7538
2018Q1123144.8602
Q2133764.372
Q3196251.956
Q4280054.067
Order Date (Year)Order Date (Quarter of Year)CategorySales
2015Q1Technology37262.974
Q2Technology27231.275
Q3Technology47751.366
Q4Technology63032.618
2016Q1Technology18418.246
Q2Technology29239.318
Q3Technology44912.726
Q4Technology70210.519
2017Q1Technology39446.832
Q2Technology60095.345
Q3Technology45824.808
Q4Technology80997.195
2018Q1Technology56188.699
Q2Technology43011.075
Q3Technology67771.691
Q4Technology104759.346
2015Q1Office Supplies14528.683
Q2Office Supplies31243.735
Q3Office Supplies53923.968
Q4Office Supplies52080.026
2016Q1Office Supplies23059.394
Q2Office Supplies32320.041
Q3Office Supplies35760.814
Q4Office Supplies46093.214
2017Q1Office Supplies29440.963
Q2Office Supplies34584.459
Q3Office Supplies45147.922
Q4Office Supplies74766.638
2018Q1Office Supplies43232.347
Q2Office Supplies45721.194
Q3Office Supplies72197.163
Q4Office Supplies84946.471
2015Q1Furniture22656.139
Q2Furniture28063.7496
Q3Furniture41957.8783
Q4Furniture64515.0862
2016Q1Furniture27374.0986
Q2Furniture27564.828
Q3Furniture49586.0352
Q4Furniture65993.2752
2017Q1Furniture24349.386
Q2Furniture41402.497
Q3Furniture52814.6322
Q4Furniture80334.9208
2018Q1Furniture23723.8142
Q2Furniture45032.103
Q3Furniture56283.102
Q4Furniture90348.25
Order Date (Year)Order Date (Month of Year)Profit
2015December8983.5699
2016December8016.9659
2017December17885.3093
2018December8483.3468
2015November9292.1269
2016November12474.7884
2017November4011.4075
2018November9690.1037
2015October3448.2573
2016October2817.366
2017October16243.1425
2018October9275.2755
2015September8328.0994
2016September8209.1627
2017September9328.6576
2018September10991.5556
2015August5318.105
2016August5355.8084
2017August2062.0693
2018August9040.9557
2015July-841.4826
2016July3288.6483
2017July4432.8779
2018July6952.6212
2015June4976.5244
2016June3335.5572
2017June4750.3781
2018June8223.3357
2015May2738.7096
2016May4667.869
2017May8662.1464
2018May6342.5828
2015April3488.8352
2016April4187.4962
2017April2977.8149
2018April933.29
2015March498.7299
2016March9732.0978
2017March3611.968
2018March14751.8915
2015February862.3084
2016February2813.8508
2017February5004.5795
2018February1613.872
2015January2450.1907
2016January-3281.007
2017January2824.8233
2018January7140.4391
YearStateValue
2016Alabama22.3
Alaska25.5
Arizona28
Arkansas18.8
Average27.17
California31.7
2017Alabama32.2
Alaska24.5
Arizona24.3
Arkansas30.1
Average26.99
California24
Date11/3/201311/4/201311/5/201311/8/201311/13/201311/14/201311/18/201311/19/201311/24/201311/27/201311/29/201312/1/2013
StatusCountCountCountCountCountCountCountCountCountCountCountCount
Close646665616659636058626658
High596259585866606661636466
Low606462625861586360595965
Open605961595958586060616160
Fan Chart
YearQuarterDiff from Monthly AvgForecastHighBoundLowBound
2015Q1-138255000
Q2-114072000
Q3118000
Q472106000
2016Q1-149447000
Q2-108901000
Q3-26631000
Q477443000
2017Q1-100676000
Q2-14986000
Q3424000
Q4185047000
2018Q1-40860000
Q2-19621000
Q3105354000
Q4272958272960272960272960
2019Q102885586346-28636
Q2066948138812-4916
Q3015097523478367167
Q40272897367146178647
2020Q1028853139224-81515
Q2066948185442-51545
Q3015097327707024880
Q40272323406161139633
NameBornDiedLife
Haydn03-31-173205-31-180928,184
Mozart01-27-175612-05-179113,096
Beethoven12-17-177003-26-182720,552
Schubert01-31-179711-19-182811,614
Berlioz12-11-180303-08-186923,829
Schumann06-08-181007-29-185616,853
Brahms05-07-183304-03-189723,342
Elgar06-02-185706-23-193428,144
RegionOrder Date (Quarter)Sales
CentralQ1, 20158600.682
Q2, 201517407.1446
Q3, 201544171.4468
Q4, 201533658.8912
Q1, 201611768.3656
Q2, 201623979.145
Q3, 201624485.5382
Q4, 201642641.1732
Q1, 201720211.697
Q2, 201725759.465
Q3, 201733380.2242
Q4, 201768077.9898
Q1, 201840530.0572
Q2, 201827938.739
Q3, 201832468.947
Q4, 201846160.385
EastQ1, 20156579.338
Q2, 201521064.165
Q3, 201533443.383
Q4, 201567593.571
Q1, 201617145.868
Q2, 201622703.208
Q3, 201650777.423
Q4, 201665705.558
Q1, 201724774.765
Q2, 201752166.657
Q3, 201738051.646
Q4, 201765692.754
Q1, 201818051.762
Q2, 201831511.5
Q3, 201865496.387
Q4, 201898023.255
SouthQ1, 201544262.199
Q2, 201522524.103
Q3, 201516061.0615
Q4, 201520998.48
Q1, 201616444.443
Q2, 201616254.2045
Q3, 201621459.505
Q4, 201617201.828
Q1, 201723933.704
Q2, 201718381.828
Q3, 201721635.8805
Q4, 201729658.811
Q1, 201813642.182
Q2, 201829325.4145
Q3, 201823874.152
Q4, 201856064.109
WestQ1, 201515005.577
Q2, 201525543.347
Q3, 201549957.321
Q4, 201557376.788
Q1, 201623493.062
Q2, 201626187.6295
Q3, 201633537.109
Q4, 201656748.449
Q1, 201724317.015
Q2, 201739774.351
Q3, 201750719.6115
Q4, 201772669.199
Q1, 201850920.859
Q2, 201844988.7185
Q3, 201874412.47
Q4, 201879806.318
LineThe standard way to show a changing time series. If data are irregular, consider markers to represent data points.Line+ColumnColumns work well for showing change over time - but usually best with only one series of data at a time.ColumnArea ChartUse with care – these are good at showing changes to total, but seeing change in components can be very difficult.Calendar HeatmapA great way of showing temporal patterns at the expense of showing precision in quantity.SlopeGood for showing changing data as long as the data can be simplified into 2 or 3 points without missing a key part of story.Candle StickUsually focused on day to day activity, these chart show open/close and hi/low points dailyFan ChartUse to show the uncertainty in future projections - usually this grows the further forward to projection.Priestley TimelineGreat when date and duration are key elements of the story in the data.Circle TimelineGood for showing discrete values of varying size across multiple categories (e.g., sales by quarter).Change over TimeGive emphasis to changing trends. These can be short movements or extended series traversing decades:Choosing the correct time period is important to provide suitable context for the reader.