vDataFrame.merge_similar_names¶

In [ ]:

vDataFrame.merge_similar_names(skip_word: list)

Merges columns with similar names. The function generates a COALESCE statement that merges the columns into a single column that excludes the input words. Note that the order of the variables in the COALESCE statement is based on the order of the 'get_columns' method.

Parameters¶

Name	Type	Optional	Description
skip_word	list	❌	List of words to exclude from the provided column names. For example, if two columns are named 'age.information.phone' and 'age.phone' AND skip_word is set to ['.information'], then the two columns will be merged together with the following COALESCE statement: COALESCE("age.phone", "age.information.phone") AS "age.phone"

Returns¶

vDataFrame : An object containing the merged element.

Example¶

In [1]:

from verticapy.utilities import tablesample
x = tablesample(
    {
        "age": [50, None, None, None],
        "information.age": [None, None, 30, None],
        "dict.age": [None, 80, None, None],
        "age.people": [None, None, None, 10],
        "num": [1, 2, 3, 4],
    }
).to_vdf()
x

Out[1]:

	123 age Integer	123 information.age Integer	123 dict.age Integer	123 age.people Integer	123 num Integer
1	50	[null]	[null]	[null]	1
2	[null]	[null]	80	[null]	2
3	[null]	30	[null]	[null]	3
4	[null]	[null]	[null]	10	4

Rows: 1-4 | Columns: 5

In [2]:

x.merge_similar_names(skip_word=["information.", "dict.", ".people"])

Out[2]:

	123 age Integer	123 num Integer
1	50	1
2	80	2
3	30	3
4	10	4

Rows: 1-4 | Columns: 2