the president of China or Japan (hoping for panda)

idiocracy23.blogspot.com/2022/08/1001...
“A combination of Bukowski’s Last Night of the Earth and Orwell’s 1984.”

#comedy #jokes #funny #humor #GregGutfeld #FoxNews #Trump #China #XiJinping #Japan #FBI #pandas #RFK #SpongeBob

Coming to #Python #Pandas from NumPy? You'll reach for np.isnan:

s = Series([10, np.nan, 30])
s.loc[ ~np.isnan(s) ] # returns 10, 30

Unfortunately, this works. Better, use s.isna (or s.isnull).

But the best way to drop NaN? Use dropna:

s.dropna() # returns 10, 30

El chino le regaló 2 #pandas al gringo.

Want to write NaN in #Python #Pandas, but are annoyed that NumPy removed it? Or: Tired of importing NumPy, just for np.nan?

I learned *yesterday* that you can say:

float('nan') or float('NaN')

Both return a perfectly usable NaN, good in NumPy and Pandas.

Wow. 🤯

How often are AI incidents happening? Are they becoming more frequent? Who is getting harmed?

In the latest Bamboo Weekly, we analyze the AI incident database using #Python #Pandas — plus joins, JSON, pivot tables, and Plotly.

More info: buff.ly/BO8uMFy

PyArrow dtypes in #Python #Pandas are nullable (with pd.NA):

s = Series([10, pd.NA, 30], dtype='int64[pyarrow]')

s is:

0 10
1 <NA>
2 30
dtype: int64[pyarrow]

The dtype is int64, but allows nulls. (Use np.nan? It's turned into pd.NA.)

TDD EP#272 | TOCA POSTAL SELO #15: O Panda e o Descascarralho! #tocadodragao #2026 #podcast #leituradeemails #pandas #alho #descascador #comedia #zoeira #piadas #humorduvidoso open.spotify.com/episode/7f3U...

You have a #Python #Pandas series with ints + NaN. You don't want float forced on you.

Solution: Use the "extension" type Int64 (note Initial Caps) and pd.NA:

s = Series([10, pd.NA, 30], dtype='Int64') # must name explicitly

s is:

0 10
1 <NA>
2 30
dtype: Int64

260 lines of Python that dedupe messy CSVs using fuzzy matching on any key column. For anyone merging CRM exports or mailing lists. Intermediate.

https://www.valtersit.com/python/csv-deduplicator-with-fuzzy-matching/

#python #data #pandas

Pretty sure if #skynet got loose today, it would run some janky #pandas / #python script, not 6502 assembly code..

Values in a #Python #Pandas series all have the same dtype.

np.nan is a float, so (1) the series gets a float dtype, or
(2) it's "object," meaning "something unspecific."

Annoying for integers. Awful for other types.

For this, we need nullable types! (Coming tomorrow...)

Missing data? NumPy calls it nan. #Python #Pandas displays it as NaN.

But: Pandas doesn't define pd.nan or pd.NaN. NumPy removed np.NaN in version 2.0.

So you have to refer to np.nan from within Pandas, and it'll be displayed as NaN.

using google colab to learn me some #pandas

mypetflamingo.bandcamp.com/album/constant

NumPy is very strict about nan. But #Python #Pandas throws nan values away:

s = Series([10, 20, 30, np.nan, 50])
s.sum() # np.float64(110.0)
s.mean() # np.float64(27.5)
s.count() # np.int64(4)

Get stricter behavior with skipna=False:

s.sum(skipna=False) # np.float64(nan)

Missing data in #Python #Pandas? We use nan ("not a number"), which comes from NumPy.

np.nan is a float, but not a normal one:

np.nan + 10 # nan
np.nan * 12345 # nan
sum([10, 20, np.nan]) # nan
np.nan == 0 # False
np.nan == np.nan # False

Solved 🙌 some codingbat py_ yesterday

Opening a #pandas tutorial via #Gemini

Play around, buddy; it's baked in! 👨‍💻👨‍🍳

How are the schools in your country?

The results from PISA 2025 are out, ranking education systems in dozens of countries.

In the latest Bamboo Weekly, we use #Python #Pandas to better understand some of this data.

Level up your data-analysis skills every Wednesday: buff.ly/cMTVKZf

Copenhagen Zoo’s seventh panda breeding attempt fails #CopenhagenZoo #denmark #pandas