A row in
DataFrame. The fields in it can be accessed:
like attributes (
like dictionary values (
key in rowwill search through row keys.
Row can be used to create a row object by using named arguments. It is not allowed to omit a named argument to represent that the value is None or missing. This should be explicitly set to None in this case.
Rows created from named arguments no longer have field names sorted alphabetically and will be ordered in the position as entered.
>>> row = Row(name="Alice", age=11) >>> row Row(name='Alice', age=11) >>> row['name'], row['age'] ('Alice', 11) >>> row.name, row.age ('Alice', 11) >>> 'name' in row True >>> 'wrong_key' in row False
Row also can be used to create another Row like class, then it could be used to create Row objects, such as
>>> Person = Row("name", "age") >>> Person <Row('name', 'age')> >>> 'name' in Person True >>> 'wrong_key' in Person False >>> Person("Alice", 11) Row(name='Alice', age=11)
This form can also be used to create rows as tuple values, i.e. with unnamed fields.
>>> row1 = Row("Alice", 11) >>> row2 = Row(name="Alice", age=11) >>> row1 == row2 True
Return as a dict
Return number of occurrences of value.
index(value[, start, stop])
Return first index of value.