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I'm learning julia from https://docs.juliaplots.org/latest/basics/ Here is the julia code
using Plots,UnicodePlots,RDatasets
unicodeplots()
v=dataset("Ecdat","Airline")
typeof(v)
plot(v, :Cost) # this line will produce the error
plot(v) # this line will produce the error, too
I got
ERROR: Cannot convert DataFrame to series data for plotting
Stacktrace:
[1] prepareSeriesData(::DataFrame) at /home/dlin/.julia/packages/Plots/qZHsp/src/series.jl:14
[2] convertToAnyVector(::DataFrame, ::Dict{Symbol,Any}) at /home/dlin/.julia/packages/Plots/qZHsp/src/series.jl:26
[3] macro expansion at /home/dlin/.julia/packages/Plots/qZHsp/src/series.jl:130 [inlined]
[4] apply_recipe(::Dict{Symbol,Any}, ::Type{Plots.SliceIt}, ::Nothing, ::DataFrame, ::Nothing) at /home/dlin/.julia/packages/RecipesBase/zBoFG/src/RecipesBase.jl:275
[5] _process_userrecipes(::Plots.Plot{Plots.GRBackend}, ::Dict{Symbol,Any}, ::Tuple{DataFrame}) at /home/dlin/.julia/packages/Plots/qZHsp/src/pipeline.jl:83
[6] _plot!(::Plots.Plot{Plots.GRBackend}, ::Dict{Symbol,Any}, ::Tuple{DataFrame}) at /home/dlin/.julia/packages/Plots/qZHsp/src/plot.jl:178
[7] #plot#138(::Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}}, ::typeof(plot), ::DataFrame) at /home/dlin/.julia/packages/Plots/qZHsp/src/plot.jl:57
[8] plot(::DataFrame) at /home/dlin/.julia/packages/Plots/qZHsp/src/plot.jl:51
[9] top-level scope at REPL[4]:1
In the code of series.jl, it is
prepareSeriesData(x) = error("Cannot convert $(typeof(x)) to series data for plotting")
How to correct this?
607
Single row in the DataFrame into a Series (1) Convert a Single DataFrame Column into a Series To start with a simple example, let’s create a DataFrame with a single column: import pandas as pd data = {'First_Name': ['Jeff','Tina','Ben','Maria','Rob']} df = pd.DataFrame (data, columns = ['First_Name']) print (df) print (type (df))
You can convert Pandas DataFrame to a Series using squeeze: In this guide, you’ll see 3 scenarios of converting: To start with a simple example, let’s create a DataFrame with a single column:
The PyPlots module provides a Julia interface to the Matplotlib plotting library from Python. Although PyPlots is a distribution of Python and matplotlib, Julia can install a private distribution that can’t be accessed outside Julia’s environment. Open a new terminal window and run Julia.
To start with a simple example, let’s create a DataFrame with a single column: Run the code in Python, and you’ll get the following DataFrame (note that print (type (df)) was added at the bottom of the code to demonstrate that we got a DataFrame):
What about simply using plot(v.Cost):
julia> plot(v.Cost)
┌────────────────────────────────────────────────────────────┐
4.88870026e6 │⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⣠⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀│ y1
│⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀│
│⠀⡇⠀⠀⠀⠀⠀⠀⠀⢰⢹⠀⠀⠀⠀⠀⠀⠀⠀⢀⡄⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀│
│⠀⡇⠀⠀⠀⠀⠀⠀⠀⡎⢸⠀⠀⠀⠀⠀⠀⠀⠀⡸⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀│
│⠀⡇⠀⠀⠀⠀⠀⢀⠎⠀⢸⠀⠀⠀⠀⠀⠀⠀⢠⠃⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀│
│⠀⡇⠀⠀⠀⠀⠀⢸⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⡇⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀│
│⠀⡇⠀⠀⠀⠀⠀⡎⠀⠀⢸⠀⠀⠀⠀⠀⠀⢸⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀│
│⠀⡇⠀⠀⠀⠀⠀⡇⠀⠀⢸⠀⠀⠀⠀⠀⠀⡎⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀│
│⠀⡇⠀⠀⠀⠀⢰⠁⠀⠀⢸⠀⠀⠀⠀⠀⠀⡇⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀│
│⠀⡇⠀⠀⠀⠀⡸⠀⠀⠀⢸⠀⠀⠀⠀⠀⢰⠁⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀│
│⠀⡇⠀⠀⠀⢀⠇⠀⠀⠀⢸⠀⠀⠀⠀⠀⢸⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀│
│⠀⡇⠀⠀⠀⡼⠀⠀⠀⠀⠈⡆⠀⠀⠀⠀⡇⠀⠀⠀⢣⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀│
│⠀⡇⠀⠀⡰⠁⠀⠀⠀⠀⠀⡇⠀⠀⠀⢰⠁⠀⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀│
│⠀⡇⠀⡰⠁⠀⠀⠀⠀⠀⠀⡇⠀⠀⢠⠇⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀│
│⠀⡇⡰⠁⠀⠀⠀⠀⠀⠀⠀⡇⠀⢀⠇⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⣀⠀⠀⠀⠀⠀⠀⠀⢀⠜⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀│
│⠀⡏⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⡎⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀⢀⠜⠊⢸⠀⠀⠀⠀⠀⠀⢀⠎⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡄⠀│
│⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⡼⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⢠⠋⠀⠀⢸⠀⠀⠀⠀⠀⠀⡎⠀⠀⢱⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡜⠀⠀│
│⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠋⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⡠⠒⠁⠀⠀⠀⠀⡇⠀⠀⠀⢀⠜⠀⠀⠀⢸⠀⠀⠀⠀⠀⠀⡠⠔⢲⠀⠀⠀⠀⠀⠀⠀⡔⠁⠀⠀│
│⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠸⠒⠊⠀⠀⠀⠀⠀⠀⠀⡇⡠⠖⠉⠁⠀⠀⠀⠀⢸⠀⠀⠀⢀⡠⠒⠁⠀⠈⡆⠀⠀⠀⠀⡠⠎⠀⠀⠀⠀│
-71402.26000000001 │⠤⡧⠤⠤⠤⠤⠤⠤⠤⠤⠤⠤⠤⠤⠤⠤⠤⠤⠤⠤⠤⠤⠤⠤⠤⠤⠤⠤⠤⠤⠭⠤⠤⠤⠤⠤⠤⠤⠤⠼⠶⠾⠭⠥⠤⠤⠤⠤⠤⠷⠶⠾⠭⠭⠤⠤⠤⠤⠤⠤│
└────────────────────────────────────────────────────────────┘
-1.67 92.67
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