Rename column if its name matches to a name in given list

In Julia, there are multiple ways to rename a column if its name matches a name in a given list. Here, we will explore three different approaches to solve this problem.

Approach 1: Using DataFrames.jl

The first approach involves using the DataFrames.jl package, which provides a convenient way to manipulate tabular data. We can use the `rename!` function to rename the column if its name matches any name in the given list.

using DataFrames

function rename_column(df::DataFrame, column_names::Vector{String}, new_name::String)
    for col in names(df)
        if col in column_names
            rename!(df, Symbol(col) => Symbol(new_name))
        end
    end
    return df
end

# Example usage
df = DataFrame(A = 1:3, B = 4:6, C = 7:9)
column_names = ["B", "C"]
new_name = "RenamedColumn"

rename_column(df, column_names, new_name)

This approach iterates over each column name in the DataFrame and checks if it matches any name in the given list. If a match is found, the column is renamed using the `rename!` function. This approach modifies the DataFrame in-place.

Approach 2: Using DataFramesMeta.jl

The second approach involves using the DataFramesMeta.jl package, which provides a more concise syntax for data manipulation. We can use the `@transform` macro to rename the column if its name matches any name in the given list.

using DataFrames, DataFramesMeta

function rename_column(df::DataFrame, column_names::Vector{String}, new_name::String)
    @transform(df, new_name = ifelse.(colname -> colname in column_names, new_name, :colname))
end

# Example usage
df = DataFrame(A = 1:3, B = 4:6, C = 7:9)
column_names = ["B", "C"]
new_name = "RenamedColumn"

rename_column(df, column_names, new_name)

This approach uses the `@transform` macro to create a new column with the desired name if the column name matches any name in the given list. Otherwise, it keeps the original column name. This approach creates a new DataFrame with the renamed column.

Approach 3: Using DataFramesMeta.jl and DataFramesMetaExtensions.jl

The third approach combines the use of DataFramesMeta.jl and DataFramesMetaExtensions.jl packages. DataFramesMetaExtensions.jl provides additional functionality to DataFramesMeta.jl, including the ability to rename columns using a more intuitive syntax.

using DataFrames, DataFramesMeta, DataFramesMetaExtensions

function rename_column(df::DataFrame, column_names::Vector{String}, new_name::String)
    @transform(df, new_name = rename(colname => new_name) for colname in column_names)
end

# Example usage
df = DataFrame(A = 1:3, B = 4:6, C = 7:9)
column_names = ["B", "C"]
new_name = "RenamedColumn"

rename_column(df, column_names, new_name)

This approach uses the `@transform` macro along with the `rename` function from DataFramesMetaExtensions.jl to rename the columns specified in the given list. This approach creates a new DataFrame with the renamed column.

Among the three options, the best approach depends on the specific requirements of the problem. If you prefer a simple and straightforward solution, Approach 1 using DataFrames.jl is a good choice. If you prefer a more concise syntax, Approach 2 using DataFramesMeta.jl is a good option. If you want additional functionality and a more intuitive syntax, Approach 3 using both DataFramesMeta.jl and DataFramesMetaExtensions.jl is recommended.