# DataFrame grouped by a column; How to access a group by a particular value in that column

**URL:** <https://discourse.julialang.org/t/dataframe-grouped-by-a-column-how-to-access-a-group-by-a-particular-value-in-that-column/74084>\
**Category:** General Usage\
**Tags:** dataframes\
**Created:** [January 5, 2022, 12:35pm UTC](https://discourse.julialang.org/t/dataframe-grouped-by-a-column-how-to-access-a-group-by-a-particular-value-in-that-column/74084 "2022-01-05T12:35:13Z")\
**Posts on this page:** 2\
**Page:** 1

<div class="post-metadata">

**Author:** ![empet](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/empet/32/221303_2.png) [@empet](https://discourse.julialang.org/u/empet)\
**Post date:** [January 5, 2022, 12:35pm UTC](https://discourse.julialang.org/t/dataframe-grouped-by-a-column-how-to-access-a-group-by-a-particular-value-in-that-column/74084/1 "2022-01-05T12:35:13Z")

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It’s the first time when I’m working with `groupby` a DataFrame. Let us say I have a DataFrame, grouped by city name:

```julia
df=DataFrame(city=["Paris", "London", "Paris", "Berlin", "London", "Berlin", "Berlin"],  
             date= ["10-1$k-2021" for k in 3:9],
             v=38 .+100*rand(7))
gb =groupby(df, :city)

```

Is there a better method to get the list of cities associated to groups (i.e. the equivalent of pandas `gb.groups.keys()`?  
I retrieved them as follows:

```julia
city_name = String[]
for gr in gb 
   push!(city_name, gr[1, :city])
end

```

How could I access a group by its city name, not by its index? Is there a method like this pandas one:

```julia
gb.get_group("Berlin")

```

---

<div class="post-metadata">

**Author:** ![jules](https://avatars.discourse-cdn.com/v4/letter/j/41988e/32.png) [@jules](https://discourse.julialang.org/u/jules)\
**Post date:** [January 5, 2022, 12:41pm UTC](https://discourse.julialang.org/t/dataframe-grouped-by-a-column-how-to-access-a-group-by-a-particular-value-in-that-column/74084/2 "2022-01-05T12:41:59Z")

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The group keys are (named) tuples of the respective values (a one-tuple if you group by one column), so you can index into the GroupedDataFrame with such a one-tuple:

```julia
gdf = groupby(df, :city)

julia> gdf[("Berlin",)]
3×3 SubDataFrame
 Row │ city date v        
     │ String String Float64  
─────┼──────────────────────────────
   1 │ Berlin 10-16-2021 109.655
   2 │ Berlin 10-18-2021 100.57
   3 │ Berlin 10-19-2021 65.6764

```

If you like a `get_group` function better, where you can avoid the tuple syntax which is admittedly a bit ugly if there’s just one column, you could do it like this:

```julia
julia> get_group(gdf, keys...) = gdf[(keys...,)]
get_group (generic function with 1 method)

julia> get_group(gdf, "Berlin")
3×3 SubDataFrame
 Row │ city date v        
     │ String String Float64  
─────┼──────────────────────────────
   1 │ Berlin 10-16-2021 109.655
   2 │ Berlin 10-18-2021 100.57
   3 │ Berlin 10-19-2021 65.6764

```

Also, you get the keys with the `keys` function (same for normal dictionaries or any other key-based datastructure in Julia, usually)

```julia
julia> keys(gdf)
3-element DataFrames.GroupKeys{GroupedDataFrame{DataFrame}}:
 GroupKey: (city = "Paris",)
 GroupKey: (city = "London",)
 GroupKey: (city = "Berlin",)

```

You could `collect` that result if you need a vector.