ᯓ ria 🧁
Region: PH
Friday 09 October 2026 09:22:22 GMT
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Stina⭐️ :
The fact that I actually witnessed blond Phuwin irl😭💖
2026-10-09 10:56:56
11
ִ 𝅄 ᩘ ͟ꘓ꒰—ⴜᧉ𐑾𑂘¹⁰⁰⁹ ᡣ𐭩˚⋆ :
The long hair💔 tho
2026-10-09 10:14:10
8
˗ˏˋ⋆ riri ⋆ˎˊ˗ :
phuwin bring back the blonde again☹️
2026-10-09 19:18:30
0
yh :
his blonde era was a trial😭
2026-10-09 09:36:42
0
mimi 🥢 :
the caption is so real because gem suggested that he should keep it longer especially for starlympics.. phu why 💔
2026-10-09 09:30:40
92
phuwin's left toe :
I LOVE ALL OF HIS ERAS BUT HIS BLONDE ERA WAS SO ICONIC 😭😭 he really pulled it off so good
2026-10-09 09:32:49
29
Rose :
Now we got blonde joong tho
2026-10-09 11:46:17
3
kkyxraa :
wdym its a ONE TIME thinggg😭💔
2026-10-09 12:11:05
1
FeroWidi :
will be miss phuphu with blonde hair
2026-10-09 10:21:50
5
S A D I E :
he looked so hot with blonde hair 💔💔
2026-10-09 12:20:43
1
Meag :
I'll miss the blonde.
2026-10-09 15:46:01
0
miffy ‹𝟹 :
missing it already 😢😢
2026-10-09 14:05:31
0
Nan 💚❤️ :
Duró tan poco 😭
2026-10-09 15:05:11
0
katheandrea :
suertuda me siento de haber visto ese pelo rubio🥹🥹🥹❣️
2026-10-09 14:29:39
0
phuwin's left toe :
so that means we'll get black haired phuwin for tms?.. 👀 he said work
2026-10-09 09:33:05
13
mimi 🥢 :
WHY SO SOON
2026-10-09 09:30:17
5
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![If you're working with data in Python, Pandas is a must-know library. It makes data manipulation easy and efficient. These are 9 essential Pandas operations you should know: 1. Read data – Load CSV, Excel, or JSON files using pd.read_csv() or pd.read_excel(). 2. View data – Use .head() and .tail() to quickly check the first and last rows. 3. Filter rows – Apply conditions with .loc[] and .query() to extract relevant data. 4. Select columns – Pick specific columns using df[['column1', 'column2']]. 5. Handle missing values – Fill or drop missing data with .fillna() and .dropna(). 6. Group and aggregate – Summarize data using .groupby() and .agg(). 7. Sort data – Arrange values in order with .sort_values(by='column'). 8. Merge datasets – Combine multiple DataFrames with .merge() or .concat(). 9. Apply functions – Use .apply() to transform data efficiently. Mastering these operations will make working with data faster and smoother. #dataanalyst #dataanalytics #python](/video/cover/7504113882189860126.webp)
