Is it possible to set a chosen column as index in a julia dataframe?

Question

dataframes in pandas are indexed in one or more numerical and/or string columns. Particularly, after a groupby operation, the output is a dataframe where the new index is given by the groups.

Similarly, julia dataframes always have a column named Row which I think is equivalent to the index in pandas. However, after groupby operations, julia dataframes don't use the groups as the new index. Here is a working example:

using RDatasets;
using DataFrames;
using StatsBase;

df = dataset("Ecdat","Cigarette");

gdf = groupby(df, "Year");

combine(gdf, "Income" => mean)

Output:

11×2 DataFrame
│ Row │ Year  │ Income_mean │
│     │ Int32 │ Float64     │
├─────┼───────┼─────────────┤
│ 1   │ 1985  │ 7.20845e7   │
│ 2   │ 1986  │ 7.61923e7   │
│ 3   │ 1987  │ 8.13253e7   │
│ 4   │ 1988  │ 8.77016e7   │
│ 5   │ 1989  │ 9.44374e7   │
│ 6   │ 1990  │ 1.00666e8   │
│ 7   │ 1991  │ 1.04361e8   │
│ 8   │ 1992  │ 1.10775e8   │
│ 9   │ 1993  │ 1.1534e8    │
│ 10  │ 1994  │ 1.21145e8   │
│ 11  │ 1995  │ 1.27673e8   │

Even if the creation of the new index isn't done automatically, I wonder if there is a way to manually set a chosen column as index. I discover the method setindex! reading the documentation. However, I wasn't able to use this method. I tried:

#create new df
income = combine(gdf, "Income" => mean)
#set index
setindex!(income, "Year")

which gives the error:

ERROR: LoadError: MethodError: no method matching setindex!(::DataFrame, ::String)

I think that I have misused the command. What am I doing wrong here? Is it possible to manually set an index in a julia dataframe using one or more chosen columns?

Answer 1

DataFrames.jl does not currently allow specifying an index for a data frame. The Row column is just there for printing---it's not actually part of the data frame.

However, DataFrames.jl provides all the usual table operations, such as joins, transformations, filters, aggregations, and pivots. Support for these operations does not require having a table index. A table index is a structure used by databases (and by Pandas) to speed up certain table operations, at the cost of additional memory usage and the cost of creating the index.

The setindex! function you discovered is actually a method from Base Julia that is used to customize the indexing behavior for custom types. For example, x[1] = 42 is equivalent to setindex!(x, 42, 1). Overloading this method allows you to customize the indexing behavior for types that you create.

The docstrings for Base.setindex! can be found here and here.

If you really need a table with an index, you could try IndexedTables.jl.