Abs
Function to get the absolute value of a number.
Returns
Returns an expression object denoting the absolute value of the input data. The data type of the resulting expression is same as that of the input.
1from fennel.expr import col
2
3expr = col("x").abs() # equivalent to col("x").num.abs()
4
5assert expr.typeof(schema={"x": int}) == int
6assert expr.typeof(schema={"x": Optional[int]}) == Optional[int]
7assert expr.typeof(schema={"x": float}) == float
8assert expr.typeof(schema={"x": Optional[float]}) == Optional[float]
9
10# can be evaluated with a dataframe
11df = pd.DataFrame({"x": pd.Series([1, -2, pd.NA], dtype=pd.Int64Dtype())})
12assert expr.eval(df, schema={"x": Optional[int]}).tolist() == [1, 2, pd.NA]
13
14with pytest.raises(ValueError):
15 expr.typeof(schema={"x": str})python
Errors
Error during typeof or eval if the input expression is not of type int,
float, optional int or optional float.
Ceil
Function in num namespace to get the ceil of a number.
Returns
Returns an expression object denoting the ceil of the input data. The
data type of the resulting expression is int if the input was int or float
or Optional[int] when the input is Optional[int] or Optional[float].
1from fennel.expr import col
2
3expr = col("x").ceil() # equivalent to col("x").num.ceil()
4assert expr.typeof(schema={"x": int}) == int
5assert expr.typeof(schema={"x": Optional[int]}) == Optional[int]
6assert expr.typeof(schema={"x": float}) == int
7assert expr.typeof(schema={"x": Optional[float]}) == Optional[int]
8
9# can be evaluated with a dataframe
10df = pd.DataFrame({"x": pd.Series([1.1, -2.3, None])})
11assert expr.eval(df, schema={"x": Optional[float]}).tolist() == [
12 2,
13 -2,
14 pd.NA,
15]
16
17with pytest.raises(ValueError):
18 expr.typeof(schema={"x": str})python
Errors
Error during typeof or eval if the input expression is not of type int,
float, optional int or optional float.
Floor
Function in num namespace to get the floor of a number.
Returns
Returns an expression object denoting the floor of the input data. The
data type of the resulting expression is int if the input was int or float
or Optional[int] when the input is Optional[int] or Optional[float].
1from fennel.expr import col
2
3expr = col("x").floor() # equivalent to col("x").num.floor()
4assert expr.typeof(schema={"x": int}) == int
5assert expr.typeof(schema={"x": Optional[int]}) == Optional[int]
6assert expr.typeof(schema={"x": float}) == int
7assert expr.typeof(schema={"x": Optional[float]}) == Optional[int]
8
9# can be evaluated with a dataframe
10df = pd.DataFrame({"x": pd.Series([1.1, -2.3, None])})
11assert expr.eval(df, schema={"x": Optional[float]}).tolist() == [
12 1,
13 -3,
14 pd.NA,
15]
16
17with pytest.raises(ValueError):
18 expr.typeof(schema={"x": str})python
Errors
Error during typeof or eval if the input expression is not of type int,
float, optional int or optional float.
Round
Function in num namespace to round a number.
Parameters
Default: 0
The number of the decimal places to round the input to.
Returns
Returns an expression object denoting the rounded value of the input data. The
data type of the resulting expression is int / Optional[int] if precision is
set to 0 or float / Optional[int] for precisions > 0.
1from fennel.expr import col
2
3expr = col("x").ceil() # equivalent to col("x").num.ceil()
4assert expr.typeof(schema={"x": int}) == int
5assert expr.typeof(schema={"x": Optional[int]}) == Optional[int]
6assert expr.typeof(schema={"x": float}) == int
7assert expr.typeof(schema={"x": Optional[float]}) == Optional[int]
8
9# can be evaluated with a dataframe
10df = pd.DataFrame({"x": pd.Series([1.1, -2.3, None])})
11assert expr.eval(df, schema={"x": Optional[float]}).tolist() == [
12 2,
13 -2,
14 pd.NA,
15]
16
17with pytest.raises(ValueError):
18 expr.typeof(schema={"x": str})python
Errors
Error during typeof or eval if the input expression is not of type int,
float, optional int or optional float.
Precision must be a non-negative integer.
To String
Function in num namespace to convert a number to a string.
Returns
Returns an expression object denoting the string value of the input data. The
data type of the resulting expression is str (or Optional[str] if the input
is an optional number).
1from fennel.expr import col
2
3expr = col("x").num.to_string()
4
5# type is str or optional str
6assert expr.typeof(schema={"x": int}) == str
7assert expr.typeof(schema={"x": Optional[int]}) == Optional[str]
8assert expr.typeof(schema={"x": float}) == str
9assert expr.typeof(schema={"x": Optional[float]}) == Optional[str]
10
11# can be evaluated with a dataframe
12df = pd.DataFrame({"x": pd.Series([1.1, -2.3, None])})
13assert expr.eval(df, schema={"x": Optional[float]}).tolist() == [
14 "1.1",
15 "-2.3",
16 pd.NA,
17]python
Errors
Error during typeof or eval if the input expression is not of type int,
float, optional int or optional float.