新建一个DataFrame并增加4列内容 using DataFrames df1 = DataFrame() df1[:clo1] = Array([1.0,2.0,3.0]) df1[:clo2] = Array([4.0,5.0,6.0]) df1[:clo3] = Array([7.0,8.0,9.0]) df1[:ID] = Array(['a','b','c']) show(df1) >>3×4 DataFrame │ Row │ clo1 │ clo2 │ clo3...
julia> combine(groupby(df, :grp), :x => mean) 2×2 DataFrame Row │ grp x_mean │ Int64 Float64 ─────┼──────────────── 1│ 1 4.0 2│ 2 3.0 在DataFrames。在jl中,GroupedDataFrame对象支持高效的键查找。因此,当您需要重复执行查找时,它表现良好。 More advanced ...
为此,我们可以使用Julia对subregions_cum-DataFrame进行排序(与在Gadfly示例中所做的一样),但VegaLite提供了使用sort属性在图形引擎中对数据进行排序的可能性。 代码语言:javascript 代码运行次数:0 运行 AI代码解释 subregions_cum|>@vlplot(title="Population by Subregion, 2019",width=600,height=300,:bar,x={:...
The first line is called the header and contains the column names. Let’s load it using the CSV and DataFrames packages. # Load in the diamonds DataFrame diamonds = DataFrame(CSV.File("data/diamonds.csv")) typeof(diamonds) Powered By DataFrame Powered By We pass the path to the CSV...
sort.jl using DataFrames df = DataFrame( Name = ["Alice", "Bob", "Clara"], Salary = [55000, 72000, 48000] ) sorted_df = sort(df, :Salary, rev=true) println(sorted_df) Thesortfunction orders the DataFrame bySalary. Therev=trueargument sorts in descending order, so Bob (72000) ap...
在下面的代码中,使用了Julia的流水线语法(|>),将regions_cum-DataFrame指定为@vlplot的输入。...为此,我们可以使用Julia对subregions_cum-DataFrame进行排序(与在Gadfly示例中所做的一样),但VegaLite提供了使用sort属性在图形引擎中对数据进行排序的可能性。...在下一步中,所有五个密度图使用column属性水平排列。
Constructors:DataFrame,DataFrame!,Tables.rowtable,Tables.columntable,Matrix,eachcol,eachrow,Tables.namedtupleiterator,empty,empty! Getting summary:size,nrow,ncol,describe,names,eltypes,first,last,getindex,setindex!,@view,isapprox,metadata,metadata!,colmetadata,colmetadata!
(df3, ["column_A" => "first_column"]) # Get rows of a data frame with distinct values in a column with unique(df, :col) unique(df3, :column_A) # Order the rows of a data frame with sort() sort(df3, :numeric_column) # Get DataFrame summary statistics with describe() ...
It is also possible to fill a DataFrame row by row. Let us construct an empty data frame with two columns (note that the first column can only contain integers and the second one can only contain strings): julia> df = DataFrame(A = Int[], B = String[]) 0×2 DataFrame Rows can...
wrangle it, or at least do some sort of manipulation on it plot it I’ve used the daily Covid-19 statistics provided by Public Health Scotland (see code for url). These get updated daily, and published after 2pm, so there may be a short period during the day when they are not avail...