{"id":7949,"date":"2024-11-07T08:22:29","date_gmt":"2024-11-07T01:22:29","guid":{"rendered":"https:\/\/mb668s.com\/cam-nang-7mb66-xoc-dia\/?p=7949"},"modified":"2024-11-07T08:22:30","modified_gmt":"2024-11-07T01:22:30","slug":"pandas-la-gi-tim-hieu-loi-ich-va-cach-hoat-dong-cua-pandas","status":"publish","type":"post","link":"https:\/\/mb668s.com\/cam-nang-7mb66-xoc-dia\/tu-van-nghe-nghiep\/pandas-la-gi-tim-hieu-loi-ich-va-cach-hoat-dong-cua-pandas","title":{"rendered":"Pandas l\u00e0 g\u00ec? T\u00ecm hi\u1ec3u l\u1ee3i \u00edch v\u00e0 c\u00e1ch ho\u1ea1t \u0111\u1ed9ng c\u1ee7a Pandas"},"content":{"rendered":"\n

Pandas l\u00e0 thu\u1eadt ng\u1eef quen thu\u1ed9c v\u1edbi d\u00e2n c\u00f4ng ngh\u1ec7 IT, l\u1eadp tr\u00ecnh vi\u00ean, c\u00f2n v\u1edbi nh\u1eefng ng\u01b0\u1eddi kh\u00e1c c\u00f3 th\u1ec3 \u00edt ho\u1eb7c kh\u00f4ng bi\u1ebft \u0111\u1ebfn. Sau \u0111\u00e2y ch\u00fang ta s\u1ebd c\u00f9ng t\u00ecm hi\u1ec3u chi ti\u1ebft Pandas l\u00e0 g\u00ec<\/strong>, l\u1ee3i \u00edch c\u1ee7a Pandas v\u00e0 c\u00e1ch th\u1ee9c ho\u1ea1t \u0111\u1ed9ng nh\u01b0 th\u1ebf n\u00e0o nh\u00e9.<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

Pandas l\u00e0 g\u00ec?<\/h2>\n\n\n\n
\n

\u201cPandas l\u00e0 t\u1eeb vi\u1ebft t\u1eaft c\u1ee7a Panel Data l\u00e0 th\u01b0 vi\u1ec7n ph\u1ea7n m\u1ec1m \u0111\u01b0\u1ee3c vi\u1ebft cho ng\u00f4n ng\u1eef l\u1eadp tr\u00ecnh Python \u0111\u1ec3 x\u1eed l\u00fd v\u00e0 ph\u00e2n t\u00edch d\u1eef li\u1ec7u\u201d<\/strong><\/p>\n<\/blockquote>\n\n\n\n

Pandas ra \u0111\u1eddi v\u00e0o n\u0103m 2008 v\u00e0 \u0111\u01b0\u1ee3c ph\u00e1t tri\u1ec3n b\u1edfi Wes McKinney. C\u00e1i t\u00ean \u201cPandas\u201d xu\u1ea5t ph\u00e1t t\u1eeb thu\u1eadt ng\u1eef trong kinh t\u1ebf l\u01b0\u1ee3ng \u201cd\u1eef li\u1ec7u b\u1ea3ng\u201d m\u00f4 t\u1ea3 c\u00e1c t\u1eadp d\u1eef li\u1ec7u g\u1ed3m c\u00e1c quan s\u00e1t trong nhi\u1ec1u kho\u1ea3ng th\u1eddi gian. Pandas \u0111\u01b0\u1ee3c c\u00e1c chuy\u00ean gia l\u1eadp tr\u00ecnh \u0111\u00e1nh gi\u00e1 cao v\u00ec cung c\u1ea5p hi\u1ec7u su\u1ea5t t\u1ed1i \u01b0u h\u00f3a cao khi m\u00e3 ngu\u1ed3n back-end \u0111\u01b0\u1ee3c vi\u1ebft b\u1eb1ng ng\u00f4n ng\u1eef l\u1eadp tr\u00ecnh C ho\u1eb7c Python.<\/p>\n\n\n\n

Pandas cung c\u1ea5p c\u1ea5u tr\u00fac v\u00e0 ho\u1ea1t \u0111\u1ed9ng d\u1eef li\u1ec7u gi\u00fap vi\u1ec7c ph\u00e2n t\u00edch v\u00e0 thao t\u00e1c d\u1eef li\u1ec7u \u0111\u01b0\u1ee3c nhanh m\u1ea1nh, linh ho\u1ea1t v\u00e0 d\u1ec5 s\u1eed d\u1ee5ng h\u01a1n. Th\u01b0 vi\u1ec7n m\u00e3 ngu\u1ed3n m\u1edf c\u1ee7ng c\u1ed1 Python b\u1eb1ng c\u00e1ch cung c\u1ea5p cho ng\u00f4n ng\u1eef l\u1eadp tr\u00ecnh (Programming Language) ph\u1ed5 bi\u1ebfn kh\u1ea3 n\u0103ng ho\u1ea1t \u0111\u1ed9ng v\u1edbi d\u1eef li\u1ec7u gi\u1ed1ng nh\u01b0 l\u00e0 b\u1ea3ng t\u00ednh, cho ph\u00e9p t\u1ea3i, thao t\u00e1c, c\u0103n ch\u1ec9nh v\u00e0 h\u1ee3p nh\u1ea5t nhanh ch\u00f3ng, b\u00ean c\u1ea1nh c\u00e1c ch\u1ee9c n\u0103ng ch\u00ednh kh\u00e1c n\u1eefa. <\/p>\n\n\n\n

Th\u01b0 vi\u1ec7n m\u00e3 ngu\u1ed3n m\u1edf (Pandas) \u0111\u01b0\u1ee3c t\u1ea1o ra gi\u1ed1ng nh\u01b0 m\u1ed9t c\u00f4ng c\u1ee5 ho\u1eb7c kh\u1ed1i x\u00e2y d\u1ef1ng c\u1ea5p cao v\u1edbi m\u1ee5c \u0111\u00edch \u0111\u1ec3 th\u1ef1c hi\u1ec7n ph\u00e2n t\u00edch th\u1ebf gi\u1edbi th\u1ef1c m\u1ed9t c\u00e1ch th\u1ef1c t\u1ebf b\u1eb1ng Python. Trong t\u01b0\u01a1ng lai, nh\u1eefng ng\u01b0\u1eddi t\u1ea1o ra th\u01b0 vi\u1ec7n m\u00e3 ngu\u1ed3n m\u1edf d\u1ef1 \u0111\u1ecbnh s\u1ebd ph\u00e1t tri\u1ec3n n\u00f3 th\u00e0nh m\u1ed9t c\u00f4ng c\u1ee5 ph\u00e2n t\u00edch v\u00e0 x\u1eed l\u00fd d\u1eef li\u1ec7u m\u00e3 ngu\u1ed3n m\u1edf m\u1ea1nh m\u1ebd v\u00e0 linh ho\u1ea1t nh\u1ea5t, ph\u00f9 h\u1ee3p v\u1edbi b\u1ea5t k\u1ef3 ng\u00f4n ng\u1eef l\u1eadp tr\u00ecnh n\u00e0o.<\/p>\n\n\n\n

S\u1eed d\u1ee5ng Pandas mang l\u1ea1i nh\u1eefng l\u1ee3i \u00edch g\u00ec?<\/h2>\n\n\n\n

Theo c\u00e1c nh\u00e0 t\u1ed5 ch\u1ee9c Python Package Index th\u00ec Pandas (th\u01b0 vi\u1ec7n m\u00e3 ngu\u1ed3n m\u1edf) mang l\u1ea1i m\u1ed9t s\u1ed1 l\u1ee3i \u00edch sau:<\/p>\n\n\n\n

– Th\u01b0 vi\u1ec7n m\u00e3 ngu\u1ed3n m\u1edf gi\u00fap vi\u1ec7c thao t\u00e1c v\u00e0 ph\u00e2n t\u00edch d\u1eef li\u1ec7u nhanh v\u00e0 hi\u1ec7u qu\u1ea3.<\/p>\n\n\n\n

– D\u1ec5 d\u00e0ng x\u1eed l\u00fd d\u1eef li\u1ec7u b\u1ecb thi\u1ebfu (bi\u1ec3u th\u1ecb b\u1eb1ng NaN) trong c\u1ea3 d\u1eef li\u1ec7u d\u1ea5u ph\u1ea9y \u0111\u1ed9ng v\u00e0 kh\u00f4ng d\u1ea5u ph\u1ea9y \u0111\u1ed9ng.<\/p>\n\n\n\n

– Pandas (Th\u01b0 vi\u1ec7n m\u00e3 ngu\u1ed3n m\u1edf) c\u00f3 th\u1ec3 l\u1ea5y d\u1eef li\u1ec7u t\u1eeb nhi\u1ec1u ngu\u1ed3n kh\u00e1c nhau.<\/p>\n\n\n\n

– Gi\u00fap c\u0103n ch\u1ec9nh d\u1eef li\u1ec7u t\u1ef1 \u0111\u1ed9ng v\u00e0 r\u00f5 r\u00e0ng: c\u00e1c \u0111\u1ed1i t\u01b0\u1ee3ng trong th\u01b0 vi\u1ec7n m\u00e3 ngu\u1ed3n m\u1edf c\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c c\u0103n ch\u1ec9nh r\u00f5 r\u00e0ng theo m\u1ed9t t\u1eadp h\u1ee3p nh\u00e3n ho\u1eb7c ch\u1ec9 c\u1ea7n b\u1ecf qua c\u00e1c nh\u00e3n v\u00e0 \u0111\u1ec3 chu\u1ed7i, DataFrame, t\u1ef1 \u0111\u1ed9ng c\u0103n ch\u1ec9nh d\u1eef li\u1ec7u trong c\u00e1c t\u00ednh to\u00e1n.<\/p>\n\n\n\n

– Ch\u1ee9c n\u0103ng nh\u00f3m m\u1ea1nh m\u1ebd, linh ho\u1ea1t gi\u00fap l\u1eadp tr\u00ecnh vi\u00ean th\u1ef1c hi\u1ec7n c\u00e1c thao t\u00e1c ph\u00e2n t\u00e1ch – \u00e1p d\u1ee5ng – k\u1ebft h\u1ee3p tr\u00ean c\u00e1c t\u1eadp d\u1eef li\u1ec7u cho c\u1ea3 vi\u1ec7c t\u1ed5ng h\u1ee3p & chuy\u1ec3n \u0111\u1ed5i d\u1eef li\u1ec7u.<\/p>\n\n\n\n

– C\u00f3 kh\u1ea3 n\u0103ng thay \u0111\u1ed5i k\u00edch th\u01b0\u1edbc linh ho\u1ea1t: Pandas c\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c ch\u00e8n v\u00e0 x\u00f3a c\u1ed9t kh\u1ecfi DataFrames v\u00e0 c\u00e1c \u0111\u1ed1i t\u01b0\u1ee3ng c\u00f3 chi\u1ec1u cao h\u01a1n.<\/p>\n\n\n\n

– Th\u01b0 vi\u1ec7n m\u00e3 ngu\u1ed3n m\u1edf trong Python gi\u00fap ph\u00e2n chia d\u1ef1a tr\u00ean nh\u00e3n th\u00f4ng minh, l\u1eadp c\u00e1c ch\u1ec9 m\u1ee5c \u01b0a th\u00edch v\u00e0 t\u1eadp h\u1ee3p c\u00e1c t\u1eadp d\u1eef li\u1ec7u l\u1edbn.<\/p>\n\n\n\n

– Gi\u00fap chuy\u1ec3n \u0111\u1ed5i d\u1eef li\u1ec7u r\u1eddi r\u1ea1c d\u1ec5 d\u00e0ng, c\u00f3 th\u1ec3 l\u1eadp ch\u1ec9 m\u1ee5c kh\u00e1c nhau trong c\u00e1c c\u1ea5u tr\u00fac d\u1eef li\u1ec7u c\u1ee7a Python v\u00e0 Numpy kh\u00e1c \u0111\u1ec3 t\u1ea1o th\u00e0nh c\u00e1c \u0111\u1ed1i t\u01b0\u1ee3ng DataFrame.<\/p>\n\n\n\n

– Pandas gi\u00fap \u0111\u1ecbnh h\u00ecnh l\u1ea1i v\u00e0 xoay v\u00f2ng c\u00e1c t\u1eadp d\u1eef li\u1ec7u m\u1ed9t c\u00e1ch linh ho\u1ea1t, h\u1ee3p nh\u1ea5t v\u00e0 n\u1ed1i c\u00e1c t\u1eadp d\u1eef li\u1ec7u tr\u1ef1c quan v\u00e0 ghi nh\u00e3n theo c\u1ea5p b\u1eadc c\u1ee7a tr\u1ee5c.<\/p>\n\n\n\n

– Nh\u1edd c\u00f3 th\u01b0 vi\u1ec7n m\u00e3 ngu\u1ed3n m\u1edf (Pandas) m\u00e0 c\u00e1c c\u00f4ng c\u1ee5 I\/O tr\u1edf n\u00ean m\u1ea1nh m\u1ebd \u0111\u1ec3 t\u1ea3i d\u1eef li\u1ec7u t\u1eeb c\u00e1c t\u1ec7p Excel, t\u1ec7p ph\u1eb3ng (CSV v\u00e0 \u0111\u01b0\u1ee3c ph\u00e2n t\u00e1ch), c\u01a1 s\u1edf d\u1eef li\u1ec7u v\u00e0 l\u01b0u\/t\u1ea3i d\u1eef li\u1ec7u \u0111\u1ecbnh d\u1ea1ng HDF5 si\u00eau nhanh.<\/p>\n\n\n\n

– Th\u01b0 vi\u1ec7n m\u00e3 ngu\u1ed3n m\u1edf Pandas cung c\u1ea5p c\u00e1c ch\u1ee9c n\u0103ng d\u00e0nh ri\u00eang cho chu\u1ed7i th\u1eddi gian: th\u1ed1ng k\u00ea c\u1eeda s\u1ed5 \u0111\u1ed9ng, t\u1ea1o ph\u1ea1m vi ng\u00e0y v\u00e0 chuy\u1ec3n \u0111\u1ed5i t\u1ea7n s\u1ed1 ho\u1eb7c thay \u0111\u1ed5i ng\u00e0y v\u00e0 \u0111\u1ed9 tr\u1ec5.<\/p>\n\n\n\n

C\u00e1ch th\u1ee9c ho\u1ea1t \u0111\u1ed9ng c\u1ee7a Pandas<\/h2>\n\n\n\n

N\u1ed9i dung \u1edf tr\u00ean \u0111\u00e3 gi\u1ea3i th\u00edch Pandas l\u00e0 g\u00ec<\/strong> v\u00e0 nh\u1eefng m\u1ee3i \u00edch c\u1ee7a n\u00f3 mang l\u1ea1i. Ti\u1ebfp theo, ch\u00fang t\u00f4i s\u1ebd tr\u00ecnh b\u00e0y chi ti\u1ebft c\u00e1ch th\u1ee9c Pandas ho\u1ea1t \u0111\u1ed9ng nh\u01b0 th\u1ebf n\u00e0o cho m\u1ecdi ng\u01b0\u1eddi c\u00f9ng bi\u1ebft.<\/p>\n\n\n\n

Trong th\u01b0 vi\u1ec7n m\u00e3 ngu\u1ed3n m\u1edf Pandas l\u00e0 DataFrames – b\u1ea3ng d\u1eef li\u1ec7u gi\u1ed1ng nh\u01b0 Array hai chi\u1ec1u. Trong \u0111\u00f3 m\u1ed7i c\u1ed9t l\u1ea1i ch\u1ee9a c\u00e1c gi\u00e1 tr\u1ecb c\u1ee7a m\u1ed9t bi\u1ebfn v\u00e0 m\u1ed7i h\u00e0ng l\u1ea1i ch\u1ee9a m\u1ed9t b\u1ed9 gi\u00e1 tr\u1ecb t\u1eeb m\u1ed7i c\u1ed9t. D\u1eef li\u1ec7u \u0111\u01b0\u1ee3c l\u01b0u tr\u1eef trong DataFrame c\u00f3 th\u1ec3 t\u1ed3n t\u1ea1i d\u1ea1ng s\u1ed1, h\u1ec7 s\u1ed1 ho\u1eb7c l\u00e0 k\u00fd t\u1ef1. Trong Pandas DataFrames \u0111\u01b0\u1ee3c coi nh\u01b0 m\u1ed9t t\u1eeb \u0111i\u1ec3n ho\u1eb7c l\u00e0 t\u1eadp h\u1ee3p c\u00e1c \u0111\u1ed1i t\u01b0\u1ee3ng chu\u1ed7i.<\/p>\n\n\n\n

Th\u01b0\u1eddng th\u00ec c\u00e1c nh\u00e0 khoa h\u1ecdc d\u1eef li\u1ec7u v\u00e0 nh\u00e2n vi\u00ean l\u1eadp tr\u00ecnh \u0111\u00e3 quen v\u1edbi ng\u00f4n ng\u1eef l\u1eadp tr\u00ecnh R cho vi\u1ec7c t\u00ednh to\u00e1n th\u1ed1ng k\u00ea. Nh\u01b0ng khi s\u1eed d\u1ee5ng sang DataFrames nh\u01b0 m\u1ed9t c\u00e1ch l\u01b0u d\u1eef li\u1ec7u trong c\u00e1c l\u01b0\u1edbi \u0111\u1ec3 c\u00f3 th\u1ec3 d\u1ec5 d\u00e0ng xem x\u00e9t t\u1ed5ng quan. \u0110i\u1ec1u n\u00e0y c\u00f3 th\u1ec3 hi\u1ec7n Pandas (th\u01b0 vi\u1ec7n m\u00e3 ngu\u1ed3n m\u1edf) ch\u1ee7 y\u1ebfu \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng cho h\u1ecdc m\u00e1y \u1edf d\u1ea1ng DataFrames.<\/p>\n\n\n\n

Th\u01b0 vi\u1ec7n m\u00e3 ngu\u1ed3n m\u1edf Pandas cho ph\u00e9p ng\u01b0\u1eddi d\u00f9ng nh\u1eadp v\u00e0 xu\u1ea5t d\u1eef li\u1ec7u theo d\u1ea1ng b\u1ea3ng v\u1edbi nhi\u1ec1u \u0111\u1ecbnh d\u1ea1ng kh\u00e1c nhau, v\u00ed d\u1ee5 nh\u01b0 t\u1ec7p JSON, CSV.<\/p>\n\n\n\n

Pandas c\u0169ng cho ph\u00e9p l\u1eadp tr\u00ecnh vi\u00ean th\u1ef1c hi\u1ec7n nhi\u1ec1u thao t\u00e1c d\u1eef li\u1ec7u kh\u00e1c nhau, th\u1ef1c hi\u1ec7n c\u00e1c t\u00ednh n\u0103ng l\u00e0m s\u1ea1ch d\u1eef li\u1ec7u g\u1ed3m t\u1ea1o c\u1ed9t d\u1eabn xu\u1ea5t, s\u1eafp x\u1ebfp, ch\u1ecdn t\u1eadp h\u1ee3p con, \u0111i\u1ec1n, thay th\u1ebf, n\u1ed1i, th\u1ed1ng k\u00ea t\u00f3m t\u1eaft v\u00e0 v\u1ebd bi\u1ec3u \u0111\u1ed3.<\/p>\n\n\n\n

L\u00fd do n\u00ean ch\u1ecdn th\u01b0 vi\u1ec7n m\u00e3 ngu\u1ed3n m\u1edf Pandas<\/h2>\n\n\n\n

M\u1ee5c ti\u00eau c\u1ee7a Pandas (th\u01b0 vi\u1ec7n m\u00e3 ngu\u1ed3n m\u1edf) l\u00e0 tr\u1edf th\u00e0nh kh\u1ed1i c\u0103n b\u1ea3n (building block) c\u1ea5p cao c\u01a1 b\u1ea3n \u00e1p d\u1ee5ng cho c\u00f4ng vi\u1ec7c th\u1ef1c t\u1ebf, ph\u00e2n t\u00edch d\u1eef li\u1ec7u th\u1ebf gi\u1edbi th\u1ef1c trong ng\u00f4n ng\u1eef l\u1eadp tr\u00ecnh Python. V\u00e0 r\u1ed9ng h\u01a1n l\u00e0 tr\u1edf th\u00e0nh c\u00f4ng c\u1ee5 thao t\u00e1c\/ph\u00e2n t\u00edch m\u00e3 ngu\u1ed3n m\u1edf m\u1ea1nh m\u1ebd v\u00e0 linh ho\u1ea1t nh\u1ea5t c\u00f3 s\u1eb5n trong b\u1ea5t k\u1ef3 lo\u1ea1i ng\u00f4n ng\u1eef l\u1eadp tr\u00ecnh n\u00e0o. <\/p>\n\n\n\n

D\u01b0\u1edbi \u0111\u00e2y l\u00e0 nh\u1eefng l\u00fd do v\u00ec sao n\u00ean ch\u1ecdn Pandas:<\/p>\n\n\n\n

Th\u01b0 vi\u1ec7n m\u00e3 ngu\u1ed3n m\u1edf (Pandas) trong Python ph\u00f9 h\u1ee3p v\u1edbi nhi\u1ec1u lo\u1ea1i d\u1eef li\u1ec7u kh\u00e1c nhau, c\u1ee5 th\u1ec3 l\u00e0:<\/p>\n\n\n\n

+ D\u1eef li\u1ec7u d\u1ea1ng b\u1ea3ng v\u1edbi c\u00e1c c\u1ed9t \u0111\u01b0\u1ee3c nh\u1eadp kh\u00f4ng \u0111\u1ed3ng nh\u1ea5t, nh\u01b0 trong b\u1ea3ng SQL hay l\u00e0 b\u1ea3ng Excel.<\/p>\n\n\n\n

+ D\u1eef li\u1ec7u ma tr\u1eadn t\u00f9y \u00fd (c\u00f3 th\u1ec3 nh\u1eadp \u0111\u1ed3ng nh\u1ea5t ho\u1eb7c kh\u00f4ng \u0111\u1ed3ng nh\u1ea5t) gi\u1eefa nh\u00e3n h\u00e0ng v\u00e0 c\u1ed9t.<\/p>\n\n\n\n

+ D\u1eef li\u1ec7u chu\u1ed7i th\u1eddi gian \u0111\u01b0\u1ee3c s\u1eafp x\u1ebfp theo th\u1ee9 t\u1ef1 v\u00e0 kh\u00f4ng th\u1ee9 t\u1ef1 (kh\u00f4ng c\u1ea7n c\u00f3 t\u1ea7n s\u1ed1 c\u1ed1 \u0111\u1ecbnh).<\/p>\n\n\n\n

+ Th\u01b0 vi\u1ec7n m\u00e3 ngu\u1ed3n m\u1edf trong Python \u0111\u01b0\u1ee3c x\u00e2y d\u1ef1ng d\u1ef1a tr\u00ean NumPy v\u1edbi hai c\u1ea5u tr\u00fac d\u1eef li\u1ec7u ch\u00ednh l\u00e0 Series (1 chi\u1ec1u) v\u00e0 Data Frame (2 chi\u1ec1u). N\u00f3 x\u1eed l\u00fd \u0111\u01b0\u1ee3c ph\u1ea7n l\u1edbn c\u00e1c tr\u01b0\u1eddng h\u1ee3p trong l\u0129nh v\u1ef1c khoa h\u1ecdc x\u00e3 h\u1ed9i, t\u00e0i ch\u00ednh, th\u1ed1ng k\u00ea v\u00e0 nhi\u1ec1u l\u0129nh v\u1ef1c k\u1ef9 thu\u1eadt.<\/p>\n\n\n\n

+ B\u1ea5t k\u1ef3 h\u00ecnh th\u1ee9c kh\u00e1c trong c\u00e1c b\u1ed9 d\u1eef li\u1ec7u quan s\u00e1t\/th\u1ed1ng k\u00ea th\u1ef1c s\u1ef1 kh\u00f4ng c\u1ea7n ph\u1ea3i \u0111\u01b0\u1ee3c d\u00e1n nh\u00e3n v\u00e0o c\u1ea5u tr\u00fac d\u1eef li\u1ec7u th\u01b0 vi\u1ec7n m\u00e3 ngu\u1ed3n m\u1edf.<\/p>\n\n\n\n

H\u01b0\u1edbng d\u1eabn c\u00e0i \u0111\u1eb7t v\u00e0 khai b\u00e1o th\u01b0 vi\u1ec7n Pandas<\/h2>\n\n\n\n

\u0110\u1ec3 c\u00e0i \u0111\u1eb7t v\u00e0 khai b\u00e1o vi\u1ec7n m\u00e3 ngu\u1ed3n m\u1edf (Pandas) trong Python, c\u00e1c b\u1ea1n h\u00e3y tham kh\u1ea3o h\u01b0\u1edbng d\u1eabn d\u01b0\u1edbi \u0111\u00e2y:<\/p>\n\n\n\n

H\u01b0\u1edbng d\u1eabn c\u00e0i \u0111\u1eb7t th\u01b0 vi\u1ec7n Pandas trong Python<\/h3>\n\n\n\n

\u0110\u1ec3 c\u00e0i \u0111\u1eb7t Pandas trong ng\u00f4n ng\u1eef Python, c\u00e1c b\u1ea1n h\u00e3y s\u1eed d\u1ee5ng pip v\u00e0 g\u00f5 c\u00e2u l\u1ec7nh: pip install pandas<\/p>\n\n\n\n

 Ho\u1eb7c c\u00e0i \u0111\u1eb7t Pandas b\u1eb1ng Anaconda<\/a> v\u1edbi c\u00e2u l\u1ec7nh: conda install pandas<\/p>\n\n\n\n

L\u01b0u \u00fd:<\/em><\/strong> Tr\u01b0\u1edbc khi c\u00e0i \u0111\u1eb7t Pandas m\u1ecdi ng\u01b0\u1eddi c\u1ea7n c\u00e0i \u0111\u1eb7t th\u01b0 vi\u1ec7n NumPy<\/a> tr\u01b0\u1edbc (n\u1ebfu nh\u01b0 b\u1ea1n c\u00e0i \u0111\u1eb7t b\u1eb1ng Anaconda th\u00ec NumPy \u0111\u00e3 c\u00f3 s\u1eb5n r\u1ed3i).<\/p>\n\n\n\n

H\u01b0\u1edbng d\u1eabn khai b\u00e1o th\u01b0 vi\u1ec7n Pandas trong Python<\/h3>\n\n\n\n

\u0110\u1ec3 khai b\u00e1o th\u01b0 vi\u1ec7n m\u00e3 ngu\u1ed3n m\u1edf (Pandas) trong Python, c\u00e1c b\u1ea1n h\u00e3y d\u00f9ng c\u00e2u l\u1ec7nh import pandas as pd. H\u00e3y nh\u1edb kh\u00f4ng n\u00ean thay \u0111\u1ed5i pd b\u1eb1ng m\u1ed9t t\u1eeb kh\u00e1c b\u1edfi c\u00e1c t\u00e0i li\u1ec7u h\u01b0\u1edbng d\u1eabn \u0111\u1ec1u \u0111\u00e3 \u0111\u01b0\u1ee3c quy \u01b0\u1edbc ng\u1ea7m nh\u01b0 v\u1eady.<\/p>\n\n\n\n

Kh\u00e1i ni\u1ec7m Pandas l\u00e0 g\u00ec<\/strong>, l\u1ee3i \u00edch v\u00e0 c\u00e1ch ho\u1ea1t \u0111\u1ed9ng c\u1ee7a Pandas nh\u01b0 th\u1ebf n\u00e0o \u0111\u00e3 \u0111\u01b0\u1ee3c gi\u1ea3i th\u00edch \u1edf tr\u00ean. Nh\u00ecn chung, Pandas l\u00e0 m\u1ed9t th\u01b0 vi\u1ec7n m\u00e3 ngu\u1ed3n m\u1edf trong Python r\u1ea5t th\u00f4ng d\u1ee5ng v\u00e0 \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng r\u1ed9ng r\u00e3i trong l\u0129nh v\u1ef1c l\u1eadp tr\u00ecnh m\u00e1y t\u00ednh \u0111\u1eb7c bi\u1ec7t l\u00e0 d\u00f9ng \u0111\u1ec3 ph\u00e2n t\u00edch, thao t\u00e1c v\u1edbi d\u1eef li\u1ec7u \u0111\u01b0\u1ee3c nhanh ch\u00f3ng h\u01a1n. H\u00e3y truy c\u1eadp v\u00e0o Mb668s.com \u0111\u1ec3 t\u00ecm hi\u1ec3u th\u00eam nhi\u1ec1u thu\u1eadt ng\u1eef kh\u00e1c nh\u00e9.<\/p>\n\n\n\n

Th\u00fay Vui<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"

Pandas l\u00e0 thu\u1eadt ng\u1eef quen thu\u1ed9c v\u1edbi d\u00e2n c\u00f4ng ngh\u1ec7 IT, l\u1eadp tr\u00ecnh vi\u00ean, c\u00f2n v\u1edbi nh\u1eefng ng\u01b0\u1eddi kh\u00e1c c\u00f3 th\u1ec3 \u00edt ho\u1eb7c kh\u00f4ng bi\u1ebft …<\/p>\n","protected":false},"author":58,"featured_media":7955,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[17],"tags":[],"class_list":["post-7949","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-tu-van-nghe-nghiep"],"_links":{"self":[{"href":"https:\/\/mb668s.com\/cam-nang-7mb66-xoc-dia\/wp-json\/wp\/v2\/posts\/7949","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/mb668s.com\/cam-nang-7mb66-xoc-dia\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mb668s.com\/cam-nang-7mb66-xoc-dia\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mb668s.com\/cam-nang-7mb66-xoc-dia\/wp-json\/wp\/v2\/users\/58"}],"replies":[{"embeddable":true,"href":"https:\/\/mb668s.com\/cam-nang-7mb66-xoc-dia\/wp-json\/wp\/v2\/comments?post=7949"}],"version-history":[{"count":1,"href":"https:\/\/mb668s.com\/cam-nang-7mb66-xoc-dia\/wp-json\/wp\/v2\/posts\/7949\/revisions"}],"predecessor-version":[{"id":7956,"href":"https:\/\/mb668s.com\/cam-nang-7mb66-xoc-dia\/wp-json\/wp\/v2\/posts\/7949\/revisions\/7956"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/mb668s.com\/cam-nang-7mb66-xoc-dia\/wp-json\/wp\/v2\/media\/7955"}],"wp:attachment":[{"href":"https:\/\/mb668s.com\/cam-nang-7mb66-xoc-dia\/wp-json\/wp\/v2\/media?parent=7949"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mb668s.com\/cam-nang-7mb66-xoc-dia\/wp-json\/wp\/v2\/categories?post=7949"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mb668s.com\/cam-nang-7mb66-xoc-dia\/wp-json\/wp\/v2\/tags?post=7949"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}