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法律研究如何在 R 中根據類別變數過濾資料框？
為了在 R 中根據類別變數過濾資料框，我們可以按照以下步驟操作：
使用內建資料集或建立一個新的資料集，並檢視資料集中的前幾行。
然後，檢視資料集中的最後幾行。
檢查資料結構。
使用 split 函式根據類別列過濾資料。
使用內建資料集
讓我們考慮一下 base R 中的 CO2 資料集：
data(CO2) head(CO2,10)
執行上述指令碼後，將生成以下輸出（由於隨機化，此輸出在您的系統上可能會有所不同）：
Grouped Data: uptake ~ conc | Plant Plant Type Treatment conc uptake 1 Qn1 Quebec nonchilled 95 16.0 2 Qn1 Quebec nonchilled 175 30.4 3 Qn1 Quebec nonchilled 250 34.8 4 Qn1 Quebec nonchilled 350 37.2 5 Qn1 Quebec nonchilled 500 35.3 6 Qn1 Quebec nonchilled 675 39.2 7 Qn1 Quebec nonchilled 1000 39.7 8 Qn2 Quebec nonchilled 95 13.6 9 Qn2 Quebec nonchilled 175 27.3 10 Qn2 Quebec nonchilled 250 37.1
檢視最後幾行
使用 tail 函式檢視 CO2 資料中的一些最後幾行：
data(CO2) tail(CO2,10)
輸出
Grouped Data: uptake ~ conc | Plant Plant Type Treatment conc uptake 75 Mc2 Mississippi chilled 500 12.5 76 Mc2 Mississippi chilled 675 13.7 77 Mc2 Mississippi chilled 1000 14.4 78 Mc3 Mississippi chilled 95 10.6 79 Mc3 Mississippi chilled 175 18.0 80 Mc3 Mississippi chilled 250 17.9 81 Mc3 Mississippi chilled 350 17.9 82 Mc3 Mississippi chilled 500 17.9 83 Mc3 Mississippi chilled 675 18.9 84 Mc3 Mississippi chilled 1000 19.9
檢查資料結構
使用 str 函式檢查 CO2 中資料的結構：
示例
data(CO2) str(CO2)
輸出
Classes ‘nfnGroupedData’, ‘nfGroupedData’, ‘groupedData’ and 'data.frame': 84 obs. of 5 variables: $ Plant : Ord.factor w/ 12 levels "Qn1"<"Qn2"<"Qn3"<..: 1 1 1 1 1 1 1 2 2 2 ... $ Type : Factor w/ 2 levels "Quebec","Mississippi": 1 1 1 1 1 1 1 1 1 1 ... $ Treatment: Factor w/ 2 levels "nonchilled","chilled": 1 1 1 1 1 1 1 1 1 1 ... $ conc : num 95 175 250 350 500 675 1000 95 175 250 ... $ uptake : num 16 30.4 34.8 37.2 35.3 39.2 39.7 13.6 27.3 37.1 ... - attr(*, "formula")=Class 'formula' language uptake ~ conc | Plant .. ..- attr(*, ".Environment")=<environment: R_EmptyEnv> - attr(*, "outer")=Class 'formula' language ~Treatment * Type .. ..- attr(*, ".Environment")=<environment: R_EmptyEnv> - attr(*, "labels")=List of 2 ..$ x: chr "Ambient carbon dioxide concentration" ..$ y: chr "CO2 uptake rate" - attr(*, "units")=List of 2 ..$ x: chr "(uL/L)" ..$ y: chr "(umol/m^2 s)"
根據類別列過濾資料框
使用 split 函式根據 Type 列過濾 CO2 資料框：
data(CO2) split(CO2,CO2$Type)
輸出
$Quebec Grouped Data: uptake ~ conc | Plant Plant Type Treatment conc uptake 1 Qn1 Quebec nonchilled 95 16.0 2 Qn1 Quebec nonchilled 175 30.4 3 Qn1 Quebec nonchilled 250 34.8 4 Qn1 Quebec nonchilled 350 37.2 5 Qn1 Quebec nonchilled 500 35.3 6 Qn1 Quebec nonchilled 675 39.2 7 Qn1 Quebec nonchilled 1000 39.7 8 Qn2 Quebec nonchilled 95 13.6 9 Qn2 Quebec nonchilled 175 27.3 10 Qn2 Quebec nonchilled 250 37.1 11 Qn2 Quebec nonchilled 350 41.8 12 Qn2 Quebec nonchilled 500 40.6 13 Qn2 Quebec nonchilled 675 41.4 14 Qn2 Quebec nonchilled 1000 44.3 15 Qn3 Quebec nonchilled 95 16.2 16 Qn3 Quebec nonchilled 175 32.4 17 Qn3 Quebec nonchilled 250 40.3 18 Qn3 Quebec nonchilled 350 42.1 19 Qn3 Quebec nonchilled 500 42.9 20 Qn3 Quebec nonchilled 675 43.9 21 Qn3 Quebec nonchilled 1000 45.5 22 Qc1 Quebec chilled 95 14.2 23 Qc1 Quebec chilled 175 24.1 24 Qc1 Quebec chilled 250 30.3 25 Qc1 Quebec chilled 350 34.6 26 Qc1 Quebec chilled 500 32.5 27 Qc1 Quebec chilled 675 35.4 28 Qc1 Quebec chilled 1000 38.7 29 Qc2 Quebec chilled 95 9.3 30 Qc2 Quebec chilled 175 27.3 31 Qc2 Quebec chilled 250 35.0 32 Qc2 Quebec chilled 350 38.8 33 Qc2 Quebec chilled 500 38.6 34 Qc2 Quebec chilled 675 37.5 35 Qc2 Quebec chilled 1000 42.4 36 Qc3 Quebec chilled 95 15.1 37 Qc3 Quebec chilled 175 21.0 38 Qc3 Quebec chilled 250 38.1 39 Qc3 Quebec chilled 350 34.0 40 Qc3 Quebec chilled 500 38.9 41 Qc3 Quebec chilled 675 39.6 42 Qc3 Quebec chilled 1000 41.4 $Mississippi Grouped Data: uptake ~ conc | Plant Plant Type Treatment conc uptake 43 Mn1 Mississippi nonchilled 95 10.6 44 Mn1 Mississippi nonchilled 175 19.2 45 Mn1 Mississippi nonchilled 250 26.2 46 Mn1 Mississippi nonchilled 350 30.0 47 Mn1 Mississippi nonchilled 500 30.9 48 Mn1 Mississippi nonchilled 675 32.4 49 Mn1 Mississippi nonchilled 1000 35.5 50 Mn2 Mississippi nonchilled 95 12.0 51 Mn2 Mississippi nonchilled 175 22.0 52 Mn2 Mississippi nonchilled 250 30.6 53 Mn2 Mississippi nonchilled 350 31.8 54 Mn2 Mississippi nonchilled 500 32.4 55 Mn2 Mississippi nonchilled 675 31.1 56 Mn2 Mississippi nonchilled 1000 31.5 57 Mn3 Mississippi nonchilled 95 11.3 58 Mn3 Mississippi nonchilled 175 19.4 59 Mn3 Mississippi nonchilled 250 25.8 60 Mn3 Mississippi nonchilled 350 27.9 61 Mn3 Mississippi nonchilled 500 28.5 62 Mn3 Mississippi nonchilled 675 28.1 63 Mn3 Mississippi nonchilled 1000 27.8 64 Mc1 Mississippi chilled 95 10.5 65 Mc1 Mississippi chilled 175 14.9 66 Mc1 Mississippi chilled 250 18.1 67 Mc1 Mississippi chilled 350 18.9 68 Mc1 Mississippi chilled 500 19.5 69 Mc1 Mississippi chilled 675 22.2 70 Mc1 Mississippi chilled 1000 21.9 71 Mc2 Mississippi chilled 95 7.7 72 Mc2 Mississippi chilled 175 11.4 73 Mc2 Mississippi chilled 250 12.3 74 Mc2 Mississippi chilled 350 13.0 75 Mc2 Mississippi chilled 500 12.5 76 Mc2 Mississippi chilled 675 13.7 77 Mc2 Mississippi chilled 1000 14.4 78 Mc3 Mississippi chilled 95 10.6 79 Mc3 Mississippi chilled 175 18.0 80 Mc3 Mississippi chilled 250 17.9 81 Mc3 Mississippi chilled 350 17.9 82 Mc3 Mississippi chilled 500 17.9 83 Mc3 Mississippi chilled 675 18.9 84 Mc3 Mississippi chilled 1000 19.9
更新時間： 2021年8月14日
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