# What is the better way to make a countplot?

**URL:** <https://discourse.julialang.org/t/what-is-the-better-way-to-make-a-countplot/78364>\
**Category:** General Usage\
**Tags:** question, plotting, dataframes, plots, statsplots\
**Created:** [March 24, 2022, 12:23am UTC](https://discourse.julialang.org/t/what-is-the-better-way-to-make-a-countplot/78364 "2022-03-24T00:23:00Z")\
**Posts on this page:** 5\
**Page:** 1

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**Author:** ![folleyz](https://avatars.discourse-cdn.com/v4/letter/f/977dab/32.png) [@folleyz](https://discourse.julialang.org/u/folleyz)\
**Post date:** [March 24, 2022, 12:23am UTC](https://discourse.julialang.org/t/what-is-the-better-way-to-make-a-countplot/78364/1 "2022-03-24T00:23:00Z")

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Hi everybody!

I’m trying to make a countplot with StatsPlots, and i’m using the code below, that works, but i want to know if have a simplest or clever way to achieve this.

```julia
begin
@df df Plots.bar(unique(df.Gender),
	[count(i->i==("Female"), df.Gender),count(i->i==("Male"), df.Gender)])
end

```

![image](https://global.discourse-cdn.com/julialang/original/3X/e/c/ec2156f196a581eb73bb6d3baa03e4a1c9becbc7.png)

The problem of my code is if have a lot of different categories like the column “Geography” i need to specify manually each category value.

Here’s a sample of my dataframe:

| | RowNumber | CustomerId | Surname | CreditScore | Geography | Gender | Age | Tenure | Balance | NumOfProducts | HasCrCard | IsActiveMember | EstimatedSalary | Exited |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | Int64 | Int64 | String31 | Int64 | String7 | String7 | Int64 | Int64 | Float64 | Int64 | Int64 | Int64 | Float64 | Int64 |
| 1 | 1 | 15634602 | Hargrave | 619 | France | Female | 42 | 2 | 0.0 | 1 | 1 | 1 | 1,01E+10 | 1 |
| | | | | | | | | | | | | | | |
| 2 | 2 | 15647311 | Hill | 608 | Spain | Female | 41 | 1 | 83807.9 | 1 | 0 | 1 | 1,13E+10 | 0 |
| | | | | | | | | | | | | | | |
| 3 | 3 | 15619304 | Onio | 502 | France | Female | 42 | 8 | 1,60E+10 | 3 | 1 | 0 | 1,14E+10 | 1 |
| | | | | | | | | | | | | | | |
| 4 | 4 | 15701354 | Boni | 699 | France | Female | 39 | 1 | 0.0 | 2 | 0 | 0 | 93826.6 | 0 |
| | | | | | | | | | | | | | | |
| 5 | 5 | 15737888 | Mitchell | 850 | Spain | Female | 43 | 2 | 1,26E+10 | 1 | 1 | 1 | 79084.1 | 0 |
| | | | | | | | | | | | | | | |

Thx!

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<div class="post-metadata">

**Author:** ![icweaver](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/icweaver/32/45764_2.png) [@icweaver](https://discourse.julialang.org/u/icweaver)\
**Post date:** [March 24, 2022, 12:56am UTC](https://discourse.julialang.org/t/what-is-the-better-way-to-make-a-countplot/78364/2 "2022-03-24T00:56:56Z")

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Oh yea, this is something that I always scratch my head on. I would be careful about doing things this way because we have to pay special attention to what order the groups should come in. On my end at least, `unique(df.Gender)` returns `[Male, Female]`, while what you have above plots the bars in the order of `[Female, Male]`, so the bar heights get swapped

We can clean this up a bit by replacing the anonymous functions with `==()` directly, and using `:column1` instead of `df.column1` because the `@df` macro is able to understand the former:

```julia
@df df_wide Plots.bar(
	unique(:Gender),
	[count(==("Male"), :Gender), count(==("Female"), :Gender)]
)

```

There is also [`groupedbar`](https://github.com/JuliaPlots/StatsPlots.jl#grouped-bar-plots) which handles grouping the bars into categories, as I think you mentioned in your other post, but it requires a fair bit of massaging the data into the right form. At this point I would just switch over to [AlgebraOfGraphics.jl](http://juliaplots.org/AlgebraOfGraphics.jl/stable/)

If you haven’t checked it out already, it’s a really handy package for making statistical plots with loads of customizability. Here’s a quick grouped barplot example:

```julia
using AlgebraOfGraphics, CairoMakie, DataFrames
# replace CairoMakie with GLMakie if not plotting from a notebook

# "wide" formatted data
df_wide = let
	N = 100
	DataFrame(
		Geography = rand(("France", "Spain", "US"), N),
		Score = rand(1:100, N),
		Group = rand('A':'D', N)
	)
end

df_long = stack(df_wide, :Score)
p = data(df_long) *
	mapping(:Geography=>"xlabel", :value=>"ylabel";
		color = :Group => "Legend title",
		dodge = :Group,
	) *
	visual(BarPlot)

draw(p)

```

 ![index](https://global.discourse-cdn.com/julialang/original/3X/3/9/3981e00f653e896e1f11ceb0ff0a57136e58b7d3.png)

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**Author:** ![yha](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/yha/32/3502_2.png) [@yha](https://discourse.julialang.org/u/yha)\
**Post date:** [March 24, 2022, 12:59am UTC](https://discourse.julialang.org/t/what-is-the-better-way-to-make-a-countplot/78364/3 "2022-03-24T00:59:38Z")

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```julia
using Plots
using StatsBase

bar(countmap(df.Gender))

```

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<div class="post-metadata">

**Author:** ![icweaver](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/icweaver/32/45764_2.png) [@icweaver](https://discourse.julialang.org/u/icweaver)\
**Post date:** [March 24, 2022, 1:24am UTC](https://discourse.julialang.org/t/what-is-the-better-way-to-make-a-countplot/78364/4 "2022-03-24T01:24:22Z")

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Nice, I didn’t know `bar` could accept dicts. This is definitely the way to go for simple count plots, haha

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<div class="post-metadata">

**Author:** ![folleyz](https://avatars.discourse-cdn.com/v4/letter/f/977dab/32.png) [@folleyz](https://discourse.julialang.org/u/folleyz)\
**Post date:** [March 24, 2022, 11:10am UTC](https://discourse.julialang.org/t/what-is-the-better-way-to-make-a-countplot/78364/5 "2022-03-24T11:10:58Z")

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Nice @yha and @icweaver !

Thx for that!