A cikin duniyar nazarin bayanai, ya zama ruwan dare a gamu da ma'aunin bayanan da ke ɗauke da tambarin lokaci. Wani lokaci, ƙila mu so mu sauƙaƙa kuma mu yi la’akari da kwanan watan, wanda zai iya zama da amfani ga dalilai daban-daban kamar nazarin abubuwan da ke faruwa, hasashe, ko gani. A cikin wannan labarin, za mu nuna muku yadda ake ** canza ginshiƙi na tambura na Pandas zuwa yau** ta amfani da Python, yana sauƙaƙa muku aiki da fahimtar bayanan ku. Za mu bi ku ta hanyar mafita, samar da bayanin mataki-mataki na lambar, da kuma zurfafa cikin wasu ɗakunan karatu da ayyuka masu alaƙa waɗanda za su iya ƙara amfanar dabarun sarrafa bayanan ku.
Canza Tambarin Lokaci zuwa Kwanan wata a Pandas
Don farawa, kuna buƙatar samun Panda shigar a cikin yanayin Python ku. Pandas babban ɗakin karatu ne mai ƙarfi wanda ke ba da sarrafa bayanai da kayan aikin bincike. Ɗaya daga cikin abubuwa mafi mahimmanci a cikin Pandas shine DataFrame, wanda ke ba ka damar sarrafawa da kuma nazarin adadi mai yawa tare da ayyuka iri-iri.
Maganganun juyar da ginshiƙin tambura na Pandas zuwa yau ya ƙunshi amfani da ma'ajin 'dt' da sifa 'kwana'. Bari mu ɗauka kun riga kuna da DataFrame tare da ginshiƙi na tambura. Lambar don yin jujjuya zai yi kama da haka:
import pandas as pd # Assuming your DataFrame is named df and the column with timestamps is 'timestamp_col' df['date_col'] = df['timestamp_col'].dt.date
Snippet lambar da ke sama ta ƙirƙiri sabon shafi mai suna 'date_col' a cikin DataFrame, kuma ya sanya ranar ɓangaren 'timestamp_col' zuwa gare ta.
Bayanin mataki-mataki na Code
Yanzu, bari mu rarraba lambar kuma mu fahimci abin da kowane ɓangaren sa yake yi.
1. Da farko, muna shigo da ɗakin karatu na Pandas ta amfani da laƙabin `pd' gama gari:
import pandas as pd
2. Na gaba, muna ɗauka cewa kun riga kuna da DataFrame `df' mai ɗauke da ginshiƙi tare da timestamp da ake kira 'timestamp_col'. Don ƙirƙirar sabon ginshiƙi tare da ɓangaren kwanan wata na waɗannan tambura kawai, muna amfani da maballin 'dt' wanda ke biye da sifa 'kwanan wata':
df['date_col'] = df['timestamp_col'].dt.date
Mai amfani da 'dt' yana ba da dama ga abubuwan kwanan wata na jerin Pandas, kamar 'shekara', 'wata', 'rana', da 'kwanan wata'. A cikin yanayinmu, mun yi amfani da sifa ta 'kwanan wata' wacce ke dawo da sashin kwanan wata na tambarin lokutan.
Kuma shi ke nan! Tare da waɗannan sauƙaƙan layukan lambar, kun sami nasarar canza ginshiƙin tambura na Pandas zuwa yau.
Pandas Library da Muhimmancinsa
Panda babban ɗakin karatu ne mai buɗe ido wanda ya zama babban jigon sarrafa bayanai da bincike a Python. Yana ba da ayyuka masu yawa, yana ba masu amfani damar tsaftacewa, canza, da kuma ganin bayanai duk cikin kayan aiki guda ɗaya. Abubuwan farko a cikin Pandas sune DataFrame da Series, waɗanda aka ƙera su don sarrafa nau'ikan bayanai daban-daban.
Abun DataFrame tebur ne mai girma biyu wanda zai iya samun ginshiƙan nau'ikan bayanai daban-daban, kamar lambobi, kirtani, kwanakin, da ƙari. Yana ba da ayyuka daban-daban don ingantaccen tambaya, gyarawa, da nazarin bayanai.
Abu na gaba, a daya bangaren, tsararru ce mai lamba daya mai girman fuska mai iya sarrafa kowane nau'in bayanai. Jerin ainihin tubalan ginin ginshiƙan DataFrame.
Sauran Ayyukan Manipulation Data Masu Amfani a cikin Pandas
Baya ga canza tambarin lokaci zuwa zamani, Pandas yana ba da wasu ayyuka masu amfani da yawa don sarrafa bayanai. Wasu daga cikin waɗannan sun haɗa da:
1. Tacewar: Lokacin da kake da babban saitin bayanai, za a iya samun yanayi inda kake son tace bayanai bisa wasu sharudda. Pandas yana ba da hanyoyi da yawa don tace bayanai, kamar `loc[]`, `iloc[]`, da `query()`.
2. Rukuni: Aikin `kungiyoyin()` yana ba ku damar tara bayanai da tara bayanai ta ginshiƙai ɗaya ko fiye, suna samar da ingantattun mafita don nazari da taƙaita bayanai.
3. Haɗuwa da Haɗuwa: Pandas yana da ginanniyar ayyuka, kamar 'haɗa()' da 'haɗa()', don haɗawa da haɗa yawancin DataFrames tare.
4. Magance Bace Data: Rubutun bayanan duniya galibi suna ƙunshe da bacewar ƙima, kuma Pandas yana ba da dabaru da yawa don magance waɗannan al'amura, kamar su `fillna()`, `dropna()`, da `interpolate()`.
Ta hanyar amfani da ɗimbin ayyuka da Pandas ke bayarwa, za ku kasance da ingantattun kayan aiki don magance ayyuka daban-daban na sarrafa bayanai da kuma buɗe bayanai masu mahimmanci daga ma'aunin bayanan ku.
