ʻO ke kumu o nā hale waihona puke Python i ka ʻepekema ʻikepili
Ma ke ao holoʻokoʻa o ka papahana, ua kū ʻo Python ma ke ʻano he ʻōlelo koho no ka ʻepekema data. Ke kumu ? ʻO kona mau hale waihona puke ikaika i hoʻolaʻa ʻia i ka ʻikepili ʻikepili. ʻO ka papa "Discover Python libraries for Data Science" ma OpenClassrooms hāʻawi iā ʻoe i kahi kaiapuni hohonu i kēia kaiaola.
Mai nā modules mua, e hoʻolauna ʻia ʻoe i nā hoʻomaʻamaʻa maikaʻi a me ka ʻike kumu e hoʻokō ai i kāu loiloi me Python. E ʻike ʻoe pehea e hiki ai i nā hale waihona puke e like me NumPy, Pandas, Matplotlib a me Seaborn ke hoʻololi i kou ala i ka ʻikepili. Na kēia mau mea hana e ʻae iā ʻoe e ʻimi, hoʻoponopono a nānā i kāu ʻikepili me ka maikaʻi ʻole a me ka pololei.
Akā ʻaʻole ʻo ia wale nō. E aʻo pū ʻoe i ke koʻikoʻi o ka hahai ʻana i kekahi mau lula maʻamau i ka wā e pili ana i ka nui o ka ʻikepili. Na kēia mau loina e kōkua iā ʻoe e hōʻoia i ka hilinaʻi a me ka pili o kāu mau loiloi.
I ka pōkole, he kono kēia papa e luʻu i ka honua hoihoi o ka ʻepekema data me Python. Inā he mea hoʻomaka ʻoe a he loea paha e nānā ana e hone i kou mau akamai, e hāʻawi kēia papa iā ʻoe i nā mea hana a me nā ʻenehana e hoʻomaikaʻi ai i ke kula.
E ʻike i ka mana o nā papa ʻikepili no ka nānā pono ʻana
I ka hiki ʻana mai i ka hoʻopunipuni a me ka nānā ʻana i ka ʻikepili i kūkulu ʻia, pono nā papa ʻikepili. A ma waena o nā mea hana i loaʻa e hana me kēia mau ʻikepili, kū ʻo Pandas ma ke ʻano he gula gula ma ka Python ecosystem.
ʻO ka papa OpenClassrooms e alakaʻi iā ʻoe i kēlā me kēia pae ma o ka hana ʻana i kāu mau papa ʻikepili mua me Pandas. Hāʻawi kēia mau ʻāpana ʻelua, ʻano like me ka array i ka maʻalahi o ka manipulation o ka ʻikepili, e hāʻawi ana i ka hoʻokaʻawale, kānana, a me ka hana hoʻohui. E ʻike ʻoe pehea e hoʻopunipuni ai i kēia mau papa ʻikepili e unuhi i ka ʻike pili, kānana ʻikepili kikoʻī a hoʻohui pū i nā kumu ʻikepili like ʻole.
Akā ʻoi aku ka Pandas ma mua o ka manipulation. Hāʻawi ka waihona i nā mea hana ikaika no ka hōʻuluʻulu ʻikepili. Inā makemake ʻoe e hana i nā hana pūʻulu, e helu i nā ʻikepili wehewehe a i ʻole e hui pū i nā waihona, ua uhi ʻo Pandas iā ʻoe.
No ka maikaʻi i ka ʻepekema data, ʻaʻole lawa ka ʻike i nā algorithm a i ʻole nā ʻenehana o ka nānā ʻana. He mea koʻikoʻi ka haku i nā mea hana e hiki ai ke hoʻomākaukau a hoʻonohonoho i ka ʻikepili. Me Pandas, loaʻa iā ʻoe kahi hoa aloha e hoʻokō i nā pilikia o ka ʻepekema data hou.
ʻO ke akamai o ka haʻi ʻana i nā moʻolelo me kāu ʻikepili
ʻAʻole pili wale ka ʻepekema ʻikepili i ka unuhi a me ka hoʻopunipuni ʻana i ka ʻikepili. ʻO kekahi o nā hiʻohiʻona hoihoi loa, ʻo ia ka hiki ke nānā i kēia ʻike, hoʻololi iā ia i mau kiʻi kiʻi e haʻi i kahi moʻolelo. ʻO kēia kahi i komo ai ʻo Matplotlib a me Seaborn, ʻelua o nā hale waihona puke hiʻona kaulana loa o Python.
ʻO ka papa OpenClassrooms e alakaʻi iā ʻoe i kahi huakaʻi ma o nā mea kupanaha o ka ʻike ʻikepili me Python. E aʻo ʻoe pehea e hoʻohana ai i ka Matplotlib e hana i nā kiʻi maʻamau, e like me nā pakuhi bar, histograms, a me nā pā hoʻopuehu. Loaʻa i kēlā me kēia ʻano pakuhi kona manaʻo a me ka pōʻaiapili o ka hoʻohana ʻana, a e alakaʻi ʻia ʻoe ma o nā hana maikaʻi loa no kēlā me kēia kūlana.
Akā ʻaʻole pau ka ʻike ʻana ma laila. ʻO Seaborn, i kūkulu ʻia ma Matplotlib, hāʻawi i nā hiʻohiʻona holomua no ka hana ʻana i nā hiʻohiʻona paʻakikī a me ka nani. ʻO nā palapala wela, nā kiʻi fiddle, a i ʻole nā ʻāpana paʻa, ua maʻalahi ʻo Seaborn i ka hana a intuitive.
