DataFrame

Builtin index · Collections & strings

result = DataFrame(name=values, ...)

Input: name, ... · Output: result

What it is

Each named argument is a column: values is either a numeric Vec / List of Str (a real column) or a scalar number/Str (broadcast to every row). Builds a Table from the named columns, in the order the arguments were written; a scalar/string column broadcasts to the row count set by whichever columns are actual vectors, and vector columns must all agree in length.

Overloads

One call shape — this function is not overloaded.

Examples

From the documentation, and run by the build -- the output and the figure below are what the engine actually produced. Simplest first.

df = DataFrame(x=[1, 2, 3], y=[4, 5, 6])
print(df.nrows)             # 3, same as nrow(df)

print(df.ncols)             # 2, same as ncol(df)

3
2

from collections-strings

df = DataFrame(id=[1, 2, 3], name=["alu", "steel", "brass"])
print(at(df, 1))                              # {id = 2, name = "steel"}

labeled = index(df, "name")
print(labeled)
grown = insert_row(df, 3, {id=4, name="glass"})
print(grown)

{id = 2, name = "steel"}
id  name 
--  -----
 1  alu  
 2  steel
 3  brass
id  name 
--  -----
 1  alu  
 2  steel
 3  brass
 4  glass

from collections-strings

df = DataFrame(x=[1, 2, 3, 4, 5], y=[10, 20, 30, 40, 50], label="sample")
print(nrow(df))            # 5

print(ncol(df))             # 3

tall = filter(df, df.x > 2)
xy = select(tall, "x", "y")
print(xy)
print(describe(df))

5
3
x   y
-  --
3  30
4  40
5  50
stat          x          y
-----  --------  ---------
count         5          5
mean          3         30
std    1.581139  15.811388
min           1         10
25%           2         20
    ... 3 more lines

from collections-strings

How it works

table(name=values, ...) / DataFrame(...) — columns come straight from the call's named arguments, in the order they were written (that's why style is an ordered Vec, not a HashMap: table column order is part of a table's identity).

From the note above this builtin in the interpreter, where the reasoning was written down as it was built.

See also

table — documented in the same entry.