added @slice_head and @slice_tail

README.md

@@ -83,7 +83,7 @@ TidierData.jl currently supports the following top-level macros:
 - `@mutate()` and `@transmute()` 
 - `@summarize()` and `@summarise()`
 - `@filter()`
-- `@slice()`, `@slice_sample()`, `@slice_min()`, and `@slice_max()`
+- `@slice()`, `@slice_sample()`, `@slice_min()`, `@slice_max()`, `@slice_head()`, and `@slice_tail()`
 - `@group_by()` and `@ungroup()`
 - `@arrange()`
 - `@pull()`

docs/examples/UserGuide/slice.jl

@@ -88,3 +88,15 @@ end
 @chain df begin 
   @slice_max(b, prop = .5)
 end
+
+# ## Slice the tail
+
+@chain df begin 
+  @slice_tail(prop = .5)
+end
+
+# ## Slice the head
+
+@chain df begin 
+  @slice_head(n = 3)
+end

src/TidierData.jl

@@ -19,7 +19,7 @@ export TidierData_set, across, desc, n, row_number, everything, starts_with, end
       as_float, as_integer, as_string, is_float, is_integer, is_string, missing_if, replace_missing, @select, @transmute, @rename, @mutate, @summarize, @summarise, @filter,
       @group_by, @ungroup, @slice, @arrange, @distinct, @pull, @left_join, @right_join, @inner_join, @full_join,
       @pivot_wider, @pivot_longer, @bind_rows, @bind_cols, @clean_names, @count, @tally, @drop_missing, @glimpse, @separate,
-      @unite, @summary, @fill_missing, @slice_sample, @slice_min, @slice_max, @rename_with
+      @unite, @summary, @fill_missing, @slice_sample, @slice_min, @slice_max, @rename_with, @slice_head, @slice_tail
 
 # Package global variables
 const code = Ref{Bool}(false) # output DataFrames.jl code?

src/docstrings.jl

@@ -2568,6 +2568,89 @@ julia> @chain df begin
    3 │       0.2       2.0        0.2
 ```
 """
+
+const docstring_slice_head =
+"""
+    @slice_head(df; n, prop)
+
+Retrieve rows in the beginning of a DataFrame.
+
+# Arguments
+- `df`: The source data frame or grouped data frame from which to slice rows.
+- `prop`: The proportion of rows to slice.
+- `n`: An optional integer argument to specify the number of rows at the beginning of the dataframe to retrieve. Defaults to 1.
+
+# Examples
+```jldoctest
+julia> df = DataFrame(
+           a = [missing, 0.2, missing, missing, 1, missing, 5, 6],
+           b = [0.3, 2, missing, 0.3, 6, 5, 7, 7],
+           c = [0.2, 0.2, 0.2, missing, 1, missing, 5, 6]);
+
+julia> @chain df begin
+       @slice_head(n = 3)
+       end 
+3×3 DataFrame
+ Row │ a          b          c        
+     │ Float64?   Float64?   Float64? 
+─────┼────────────────────────────────
+   1 │ missing          0.3       0.2
+   2 │       0.2        2.0       0.2
+   3 │ missing    missing         0.2
+
+julia> @chain df begin
+       @slice_head(prop = .25)
+       end 
+2×3 DataFrame
+ Row │ a          b         c        
+     │ Float64?   Float64?  Float64? 
+─────┼───────────────────────────────
+   1 │ missing         0.3       0.2
+   2 │       0.2       2.0       0.2
+```
+"""
+
+const docstring_slice_tail =
+"""
+    @slice_tail(df; n, prop)
+
+Retrieve rows in the beginning of a DataFrame.
+
+# Arguments
+- `df`: The source data frame or grouped data frame from which to slice rows.
+- `prop`: The proportion of rows to slice.
+- `n`: An optional integer argument to specify the number of rows at the beginning of the dataframe to retrieve. Defaults to 1.
+
+# Examples
+```jldoctest
+julia> df = DataFrame(
+           a = [missing, 0.2, missing, missing, 1, missing, 5, 6],
+           b = [0.3, 2, missing, 0.3, 6, 5, 7, 7],
+           c = [0.2, 0.2, 0.2, missing, 1, missing, 5, 6]);
+
+julia> @chain df begin
+       @slice_tail(n = 3)
+       end 
+3×3 DataFrame
+ Row │ a          b         c         
+     │ Float64?   Float64?  Float64?  
+─────┼────────────────────────────────
+   1 │ missing         5.0  missing   
+   2 │       5.0       7.0        5.0
+   3 │       6.0       7.0        6.0
+
+julia> @chain df begin
+       @slice_tail(prop = .25)
+       end 
+2×3 DataFrame
+ Row │ a         b         c        
+     │ Float64?  Float64?  Float64? 
+─────┼──────────────────────────────
+   1 │      5.0       7.0       5.0
+   2 │      6.0       7.0       6.0
+```
+"""
+
 const docstring_missing_if =
 """
     missing_if(x, value)

src/slice.jl

@@ -239,4 +239,98 @@ macro slice_min(df, exprs...)
           temp_df
       end
   end
+end
+
+"""
+$docstring_slice_head
+"""
+macro slice_head(df, exprs...)
+  expr_dict = :(Dict())
+
+  for expr in exprs
+      if @capture(expr, lhs_ = rhs_)
+          push!(expr_dict.args, :($(QuoteNode(lhs)) => $(esc(rhs))))
+      end
+  end
+  return quote
+      expr_dict = $expr_dict
+      temp_df = $(esc(df))
+      grouping_cols = Symbol[]
+
+      if temp_df isa DataFrames.GroupedDataFrame
+          grouping_cols = DataFrames.groupcols(temp_df)
+      end
+      local n = get(expr_dict, :n, 1)
+      local prop_val = get(expr_dict, :prop, 1.0) 
+      if prop_val < 0.0 || prop_val > 1.0
+          throw(ArgumentError("Prop value should be between 0 and 1"))
+      end
+      if temp_df isa DataFrames.GroupedDataFrame
+          result_dfs = []
+          for sdf in temp_df
+              local group_n = n
+              if prop_val != 1.0
+                  group_n = floor(Int, nrow(sdf) * prop_val)
+              end
+              push!(result_dfs, first(sdf, group_n))
+          end
+          temp_df = vcat(result_dfs...)
+      else
+          if prop_val != 1.0
+              n = floor(Int, nrow(temp_df) * prop_val)
+          end
+          temp_df = first(temp_df, n)
+      end
+
+      if !isempty(grouping_cols)
+          temp_df = DataFrames.groupby(temp_df, grouping_cols)
+      end
+      temp_df
+  end
+end
+
+"""
+$docstring_slice_tail
+"""
+macro slice_tail(df, exprs...)
+  expr_dict = :(Dict())
+  for expr in exprs
+      if @capture(expr, lhs_ = rhs_)
+          push!(expr_dict.args, :($(QuoteNode(lhs)) => $(esc(rhs))))
+      end
+  end
+  return quote
+      expr_dict = $expr_dict
+      temp_df = $(esc(df))
+      grouping_cols = Symbol[]
+      if temp_df isa DataFrames.GroupedDataFrame
+          grouping_cols = DataFrames.groupcols(temp_df)
+      end
+      local n = get(expr_dict, :n, 1) 
+      local prop_val = get(expr_dict, :prop, 1.0) 
+      if prop_val < 0.0 || prop_val > 1.0
+          throw(ArgumentError("Prop value should be between 0 and 1"))
+      end
+      if temp_df isa DataFrames.GroupedDataFrame
+          result_dfs = []
+          for sdf in temp_df
+              local group_n = n
+              if prop_val != 1.0
+                  group_n = floor(Int, nrow(sdf) * prop_val)
+              end
+              push!(result_dfs, last(sdf, group_n))
+          end
+          temp_df = vcat(result_dfs...)
+      else
+          if prop_val != 1.0
+              n = floor(Int, nrow(temp_df) * prop_val)
+          end
+          temp_df = last(temp_df, n)
+      end
+
+      if !isempty(grouping_cols)
+          temp_df = DataFrames.groupby(temp_df, grouping_cols)
+      end
+      temp_df
+  end
 end