When I use ibis-framework to generate SQL with pyspark dialect, I got this SQL: SELECT `t2`.`did`, `t2`.`location_timestamp`, EXPLODE(FROM_JSON(`t2`.`devices`, 'Array<String>')) AS `...

Is there any way to access other columns inside an ibis aggregate statement using across? I created a bunch of boolean columns using mutate across, but I want to sum another column (df. ...

Problem: I need to filter rows per ID. But I'd like to make it more general such that client user can provide more than 1 ID. I decided to write my code this way using the concept of %in% on SQL ...

I am experimenting with the Ibis framework: it seems a great tool to work on tables that already contain data that I need to join, filter, aggregate, etc. However, I do not find how to persist changes ...

We are planning to shift from infi.clickhouse to ibis, so I was wondering, does ibis support the migration of old schema to new like infi.clickhouse? If not, then what could be the solution to this? ...

Given a dataframe that has a column with a space: ibis.memtable({ 'colname with space': ['a', 'b', 'c'] }) I want to mutate this column. How do I reference it in the .mutate method? One way is ...

I'm trying to select columns by index just like this reference from the ibis docs: import ibis import ibis.selectors as s spotify = ibis.duckdb.connect() spotify.read_csv("hf://datasets/...

I want Query to be in this format SELECT u.name, nicknames AS nickname FROM `india.nvidia.user_table` u, UNNEST(nicknames) AS nicknames WHERE u.l is true my py file import ibis ...

I want to use Ibis to return the mean and standard deviation of each floating point numeric column in a table. How do I do that?

I have a table like this: ┏━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━━━━━━┓ ┃ country ┃ city ┃ population ┃ ┡━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━━━━━━┩ │ string │ string │ int64 ...

I have a function like this: import ibis def my_function(df): t = ibis.memtable(df) t = t.mutate(ibis._['a'] + 1) return to.to_arrow() My question is - if I pass it a pandas dataframe, ...

Say I want to do the following in Polars: df.with_columns( a_1 = pl.col('a').shift(1), a_2 = pl.col('a').shift(2), b_1 = pl.col('b').shift(1), b_2 = pl.col('b').shift(2), ) Say, ...

for a table with a list field i'm trying to call map import ibis from ibis import _ t = ibis.memtable({ 'i': [1,2,3], 'x': [[1,2],[3,5],[6,7] ] }) using the table object works: t.select(t....

I have a very large complex ibis script with a portion calculating some columns. at the end, I need to ibis.to_sql(t) to get a sql statement for my python. So I can't use pandas lets say i have this ...

Let t = ibis.memtable({'col0': [-2, -5, -1, 0, 1, 8, 7], 'col1': [0, -2, 4, 5, 6, 8, 7]}). I want to find all of the rows where col0 is any value in col1. In SQL, I might do: SELECT * FROM t WHERE ...