html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,issue,performed_via_github_app
https://github.com/simonw/sqlite-utils/issues/207#issuecomment-743966801,https://api.github.com/repos/simonw/sqlite-utils/issues/207,743966801,MDEyOklzc3VlQ29tbWVudDc0Mzk2NjgwMQ==,9599,2020-12-13T07:25:23Z,2020-12-13T07:25:23Z,OWNER,"CLI documentation: https://sqlite-utils.readthedocs.io/en/latest/cli.html#analyzing-tables

Python library documentation: https://sqlite-utils.readthedocs.io/en/latest/python-api.html#analyzing-a-column","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",763283616,
https://github.com/simonw/sqlite-utils/issues/207#issuecomment-743701697,https://api.github.com/repos/simonw/sqlite-utils/issues/207,743701697,MDEyOklzc3VlQ29tbWVudDc0MzcwMTY5Nw==,9599,2020-12-12T04:39:51Z,2020-12-12T04:39:51Z,OWNER,"CLI could be:

    sqlite-utils analyze-tables

To analyze all tables or:

    sqlite-utils analyze-tables table1 table2

To analyze specific tables.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",763283616,
https://github.com/simonw/sqlite-utils/issues/207#issuecomment-743701599,https://api.github.com/repos/simonw/sqlite-utils/issues/207,743701599,MDEyOklzc3VlQ29tbWVudDc0MzcwMTU5OQ==,9599,2020-12-12T04:38:52Z,2020-12-12T04:39:07Z,OWNER,I'll add a `table.analyze_column(column)` method which is used by the CLI tool - with a note that this is an unstable interface which may change in the future.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",763283616,
https://github.com/simonw/sqlite-utils/issues/207#issuecomment-743701422,https://api.github.com/repos/simonw/sqlite-utils/issues/207,743701422,MDEyOklzc3VlQ29tbWVudDc0MzcwMTQyMg==,9599,2020-12-12T04:37:14Z,2020-12-12T04:38:25Z,OWNER,"Prototype:
```python
from collections import namedtuple

ColumnDetails = namedtuple(""ColumnDetails"", (""column"", ""num_null"", ""num_blank"", ""num_distinct"", ""most_common"", ""least_common""))

def analyze_column(db, table, column, values=10):
    num_null = db.execute(""select count(*) from [{}] where [{}] is null"".format(table, column)).fetchone()[0]
    num_blank = db.execute(""select count(*) from [{}] where [{}] = ''"".format(table, column)).fetchone()[0]
    num_distinct = db.execute(""select count(distinct [{}]) from [{}]"".format(column, table)).fetchone()[0]
    most_common = None
    least_common = None
    if num_distinct != 1:
        most_common = [(r[0], r[1]) for r in db.execute(
            ""select [{}], count(*) from [{}] group by [{}] order by count(*) desc limit "".format(column, table, column, values)
        ).fetchall()]
        if num_distinct <= values:
            # No need to run the query if it will just return the results in revers order
            least_common = most_common[::-1]
        else:
            least_common = [(r[0], r[1]) for r in db.execute(
                ""select [{}], count(*) from [{}] group by [{}] order by count(*) limit {}"".format(column, table, column, values)
            ).fetchall()]
    return ColumnDetails(column, num_null, num_blank, num_distinct, most_common, least_common)


def analyze_table(db, table):
    for column in db[table].columns:
        details = analyze_column(db, table, column.name)
        print(details)
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",763283616,