or operator for querying

[spleshakov]

hello,

i'm working on a dataframe that looks like so (simplified):

╔═══╤═══════════════════╤═══════════════════╤═══════════════════╤═══════════════════╗
║   │ SERVICE_AREA_ID   │ ZIPCODE           │ COUNTY_CODE       │ COUNTY_NAME       ║
╟───┼───────────────────┼───────────────────┼───────────────────┼───────────────────╢
║ 0 │ MNS001            │ 55001             │ 27163             │ Washington        ║
╟───┼───────────────────┼───────────────────┼───────────────────┼───────────────────╢
║ 1 │ MNS002            │ 55001             │ 27163             │ Washington        ║
╟───┼───────────────────┼───────────────────┼───────────────────┼───────────────────╢
║ 2 │ NaN               │ 53001             │ 55117             │ Sheboygan         ║
╟───┼───────────────────┼───────────────────┼───────────────────┼───────────────────╢
║ 3 │ AC North and WI   │ 54856             │ 52030             │ Bayfield          ║
╟───┼───────────────────┼───────────────────┼───────────────────┼───────────────────╢
║ 4 │ North and WI      │ 54856             │ 52030             │ Bayfield          ║
╚═══╧═══════════════════╧═══════════════════╧═══════════════════╧═══════════════════╝

I'd like to filter it by column SERVICE_AREA_ID with values matching either MNS001 or MNS002

.query() seems to take only one condition

Is there a method to achieve this?

Thank you!

[risenW]

Hi @spleshakov , for now, there's no support for multiple conditions. But I see this is quite a useful feature, and I'll add it as a new feature.
A hacky and less efficient way, for now, will be to query and merge:

df1 = df.query({ column: "SERVICE_AREA_ID", is: "==", to: "MNS001" })
df2 = df.query({ column: "SERVICE_AREA_ID", is: "==", to: "MNS002" })
df3 = dfd.concat({ df_list: [df1, df2], axis: 0 })

[risenW]

@spleshakov This is similar to what we were discussing #179

[eduardomanuel]

Hi please see : #466 (comment)

I am trying to simulate an AND condition by querying a DF that is the result of a query. Getting an error.

Thank you!