Bao Li & Qing Bao face years at the National Zoo, where invasive artificial breeding could await them. Take action to protect these young pandas & urge their return to China. #GiantPandas #AnimalWelfare #Pandas bit.ly/4k0t1v2

Want to change the granularity when grouping on a #Python #Pandas data frame's datetime column?

Use Grouper.

For example: Here we get the mean trip_distance per 14-day period:

df.groupby(pd.Grouper(key='tpep_pickup_datetime', freq='14D'))['trip_distance'].mean()

Here are six cute pictures of red pandas. They look like they were made to be held, then left somewhere soft.
#Six #Here #Cute #Pandas #Quiet #InternationalNews #Photography #Animals #Wildlife #Nature #PhotoOfTheDay #AnimalPhotography #CuteAnimals #Pictures

If you have a datetime column in your #Python #Pandas data frame, you can groupby on the output of a dt method, such as day_name:

df.groupby(df['tpep_pickup_datetime'].dt.day_name())['trip_distance'].mean()

The above gives the mean trip_distance for each day.

Man (panda) of the hour. 9/9, Po!
#Po #KungFuPanda #Pandas

Process appending CSV rows live and push them to JSONL with pandas. 147 lines, intermediate. Good for logs, feeds, txn dumps.

https://www.valtersit.com/python/real-time-csv-stream-processor/

#python #data #pandas

If your #Python #Pandas data frame has a datetime column, you can group on a portion of that via the "dt" accessor.

For example, let's get mean trip_distance for each hour of the day:

df.groupby(df['tpep_pickup_datetime'].dt.hour)['trip_distance'].mean()

Ann Worley and her son Isaac joined families at the Texas State Capitol for PANS/PANDAS Awareness Day, meeting with lawmakers about diagnosis barriers, research and insurance coverage. In Michigan, @joegrimm.bsky.social carried the book’s cover to the Capitol. #PANS #PANDAS buff.ly/L3B8ZXN

Ann Worley and her son Isaac joined families at the Texas State Capitol for PANS/PANDAS Awareness Day, meeting with lawmakers about diagnosis barriers, research and insurance coverage. In Michigan, @joegrimm.bsky.social carried the book’s cover to the Capitol. #PANS #PANDAS buff.ly/L3B8ZXN

You can mix and match columns and methods, and also avoid a multi-index, when grouping on #Python #Pandas data frames with "agg" and kwargs:

- Each keyword is an output column name
- Each value is a tuple of (COLNAME, METHOD)

For example, agg(total_std=('total_amount', 'std'))

China’s panda diplomacy: how Beijing combines conservation and trade#China #giantpanda #Pandadiplomacy #pandas #Wildanimals

Drawing attention with #birthday #pandas; please help Dalton and his family! #mutualaid #helpsky linktr.ee/DGMeek92

Does #Python #Pandas allow multiple data columns and multiple methods?

Yes!

df.groupby('passenger_count')[['trip_distance', 'total_amount']].agg(['mean', 'std'])

The above returns a data frame. Its 4 columns are a 2-level multi-index with mean/std in the inner level.

Does #Python #Pandas allow multiple categorical columns and multiple methods?

Yes!

df.groupby(['passenger_count', 'VendorID'])['trip_distance'].agg(['mean', 'std'])

The above returns:

- A 2-column data frame (mean + std)
- A 2-level index (passenger_count + VendorID)

Drawing attention with #bitthday #pandas; please keep Britt and Topaz safe! #mutualaid #helpsky linktr.ee/hiitsbritt

Call multiple methods in a #Python #Pandas groupby with agg. Pass a list of strings (method names), and get a data frame back, one column per method.

df.groupby('passenger_count')['total_amount'].agg(['mean', 'std'])

Here, both methods (mean and std) are computed per group.

🏛️ La Porta de la Mar s’il·lumina esta nit pel #PANS #PANDAS i les famílies que hi conviuen.

Ens sumem al dia de conscienciació sobre esta realitat, que es va commemorar ahir.

🟢 Més visibilitat.
🟢 Més comprensió.
🟢 Més esperança.

✨ Imatge generada amb suport de la IA.

Drawing attention with #birthday #pandas; please keep Amparo safe! #mutualaid #helpsky linktr.ee/ayudamutuax

When a child changes overnight, parents need answers. On #PANSPANDASAwarenessDay, a new plain-language guide from @joegrimm.bsky.social and MSU journalism students (@michiganstateu.bsky.social) is coming soon: 100 Questions and Answers About PANS/PANDAS. #PANS #PANDAS

#pandas