Exploratory Data Analysis in R: Quick Dive into Data Visualization

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  • เผยแพร่เมื่อ 16 ก.ย. 2024
  • In this video, I continue on the topic of exploratory data analysis and provide a quick dive into data visualization using the R base plot functions.
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    ⭕ Timeline
    0:57 Fire up RStudio or RStudio.cloud
    1:08 Open Iris-data-understanding.R file
    1:14 Load in the Iris dataset
    1:32 Scroll to "Quick data visualization"
    1:43 Generate panel plot using plot(iris)
    2:10 Add the col argument to set color, e.g. plot(iris, col="red")
    2:57 To make a scatter plot use plot(var1, var2)
    3:07 For the Iris dataset use plot(iris$Sepal.Width, iris$Sepal.Length)
    3:51 To customize the x-axis label, add the xlab argument
    4:40 To construct a histogram for sepal width: hist(iris$Sepal.Width)
    5:54 Feature plot shows the Box plots for 4 variables as a function of 3 classes
    8:04 Quick recap and next video's topic
    ⭕ Code:
    github.com/dat...
    Note: Please excuse the spacing error at 1:32 "Quick data visualization"
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ความคิดเห็น • 18

  • @DataProfessor
    @DataProfessor  4 ปีที่แล้ว +3

    QUESTION OF THE DAY: Instead of specifying the color argument as col = 'red' what would happen if we use col = iris$Species ❓
    Try it and comment down below! 😃

    • @jasperj7846
      @jasperj7846 4 ปีที่แล้ว +1

      The different Species are plotted marked by colors ;)

  • @jasperj7846
    @jasperj7846 4 ปีที่แล้ว +5

    Amazing content! Even if you already know the stuff it's good to refresh or get some additional tricks :)

    • @DataProfessor
      @DataProfessor  4 ปีที่แล้ว

      Thanks for your kind words of inspiration!

  • @harshithkumarpedarla6233
    @harshithkumarpedarla6233 3 ปีที่แล้ว +2

    showing an error while working with featureplot "Couldn't find function with futureplot" how to overcome this?

  • @DrRehanZafar
    @DrRehanZafar 4 ปีที่แล้ว +1

    Nice explanation

    • @DataProfessor
      @DataProfessor  4 ปีที่แล้ว

      Dr Rehan Zafar Thank you Dr Rehan :)

  • @Max-wj4uu
    @Max-wj4uu 4 ปีที่แล้ว +1

    Need these videos with python implementation !!!!

    • @DataProfessor
      @DataProfessor  4 ปีที่แล้ว

      Thanks Max for your suggestion, Python tutorial series is in the plans and will be released in the near future.

  • @selamawitfentie5612
    @selamawitfentie5612 4 ปีที่แล้ว

    how can fix this error
    Error in plot.window(...) : need finite 'ylim' values
    In addition: Warning messages:
    1: In xy.coords(x, y, xlabel, ylabel, log) : NAs introduced by coercion
    2: In min(x) : no non-missing arguments to min; returning Inf
    3: In max(x) : no non-missing arguments to max; returning -Inf
    when we plotting the iris data set ?

  • @Nirkan88
    @Nirkan88 4 ปีที่แล้ว +1

    I need to do install.packages to run featurePlot, otherwise it showed an error.

    • @DataProfessor
      @DataProfessor  4 ปีที่แล้ว +1

      Thanks for sharing your pointers 😃

    • @impanasuresh983
      @impanasuresh983 3 ปีที่แล้ว +1

      hello can u please share which packages to run featurePlot?

    • @neroetal
      @neroetal 5 หลายเดือนก่อน

      @@impanasuresh983 chatGPT said "caret"

  • @abhipsatripathy3934
    @abhipsatripathy3934 4 ปีที่แล้ว

    Amazing content....Please interpret the first pair plot,the big one. What does that represent.

    • @stretch8390
      @stretch8390 3 ปีที่แล้ว

      A bit late as a reply but do you mean the matrix scatterplot at the ~1min mark? If so, the label in each row is the y axis for the graphs in that row and the label in each column is the x axis for the graphs in that column e.g. the first graph on the left in the top row will be Sepal.Width (x axis) vs Sepal.Length (y axis)... at least that is my beginner understanding!

  • @aviwejolingwenya6620
    @aviwejolingwenya6620 3 ปีที่แล้ว +1

    How do you deal with missing data?

    • @DataProfessor
      @DataProfessor  3 ปีที่แล้ว

      Hi, I made a video on this topic of handling missing data, please have a look th-cam.com/video/toRjEdNf0Hs/w-d-xo.html