Munyika yekuongorora data, zvakajairika kusangana nedatasets ine timestamps. Dzimwe nguva, isu tingangoda kurerutsa uye kungofunga chete zuva, iro rinogona kubatsira kune zvakasiyana siyana sekuongorora maitiro, kufanotaura, kana kuona. Muchikamu chino, tinokuratidza maitiro ** kushandura Pandas koramu yenguva dzenguva kuti isvike ** uchishandisa Python, zvichiita kuti zvive nyore kwauri kushanda pamwe nekunzwisisa data rako. Isu tichakufambisa iwe kuburikidza nemhinduro, topa nhanho-ne-nhanho tsananguro yekodhi, pamwe nekuongorora mune mamwe ane hukama maraibhurari uye mabasa anogona kuwedzera kubatsira hunyanzvi hwako hwekugadzirisa data.
Kushandura Timestamps kuDate muPandas
Kuti utange, iwe unofanirwa kuve uine pandas yakaiswa munzvimbo yako yePython. Pandas iraibhurari ine simba inopa data manipulation uye maturusi ekuongorora. Chimwe chezvinhu zvinonyanya kukosha muPandas iDataFrame, iyo inokubvumira kuti utore nyore uye uongorore huwandu hwe data nemabasa akasiyana-siyana.
Mhinduro yekushandura Pandas column yetimestamps kusvika parizvino inosanganisira kushandisa `dt` accessor uye `date` hunhu. Ngatifungei kuti watova neDataFrame ine koramu yematampu enguva. Kodhi yekuita shanduko inotaridzika seizvi:
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 yekodhi iri pamusoro inogadzira chinyorwa chitsva chine zita rekuti 'date_col' muDateFrame, uye inopa chikamu chedeti che'timestamp_col' kwachiri.
Tsanangudzo-nhanho-nhanho yeCode
Zvino, ngatichekei kodhi uye tinzwisise kuti chikamu chimwe nechimwe chayo chinoitei.
1. Chekutanga, tinopinza Pandas raibhurari tichishandisa zvakajairika `pd` alias:
import pandas as pd
2. Tevere, tinofungidzira kuti watova neDataFrame `df` ine koramu ine zvidhindo zvenguva inonzi 'timestamp_col'. Kugadzira koramu itsva ine chikamu chemazuva chete chezvitambi zvenguva idzi, tinoshandisa `dt` accessor inoteverwa ne `date` hunhu:
df['date_col'] = df['timestamp_col'].dt.date
The `dt` accessor inopa mukana kune datetime zvivakwa zvePandas Series, senge `gore`, `mwedzi`, `zuva`, uye `date`. Kwatiri isu, takashandisa `date` rinodzoreredza chikamu chedete chezvitambi zvenguva.
Uye ndizvozvo! Nemitsara iyi yakapfava yekodhi, iwe wakabudirira kushandura Pandas column ye timestamps kusvika nhasi.
Pandas Library uye kukosha kwayo
pandas iraibhurari yakavhurika-sosi yave chinhu chikuru chekugadzirisa data uye kuongororwa muPython. Inopa huwandu hwakasiyana hwekushanda, zvichiita kuti vashandisi vachenese, vashandure, uye vaone data mukati mechinhu chimwe chete. Zvinhu zvekutanga muPandas iDataFrame uye Series, iyo yakagadzirirwa kubata akasiyana marudzi e data.
Chinhu cheDataFrame itafura ine mativi maviri inogona kuve nemakoramu emhando dzakasiyana dze data, senhamba, tambo, misi, nezvimwe. Inopa mabasa akasiyana-siyana ekunyatso bvunza, kugadzirisa, uye kuongorora data.
Iyo Series chinhu, kune rumwe rutivi, iine-dimensional yakanyorwa array inokwanisa kubata chero mhando yedata. Series ndizvo chaizvo zvivharo zvekuvaka zveDataFrame makoramu.
Mamwe Anobatsira Data Manipulation Mabasa muPandas
Pamusoro pekushandura timestamps kusvika parizvino, Pandas inopawo mamwe akawanda anobatsira mabasa ekugadzirisa data. Zvimwe zvacho zvinosanganisira:
1. Kuchengeta: Kana uine dataset hombe, panogona kunge paine mamiriro aungade kusefa iyo data zvichienderana nemamwe mamiriro. Pandas inopa nzira dzakati wandei dzekusefa data, senge `loc[]`, `iloc[]`, uye `mubvunzo()`.
2. Mapoka: Iyo `groupby()` basa rinokutendera kuti uunganidze uye kuunganidza data neiyo imwe kana anopfuura makoramu, ichipa mhinduro dzinoshanda dzekuongorora uye kupfupisa data.
3. Kubatanidza uye Kubatanidza: Pandas ine akavakirwa-mukati mabasa, akadai `merge()` uye `join()`, yekubatanidza uye kubatanidza akawanda DataFrames pamwechete.
4. Kubata Data Isipo: Real-world datasets inowanzove ine zvisipo, uye Pandas inopa akati wandei maitiro ekuita nezviitiko izvi, senge `fillna()`, `dropna()`, uye `interpolate()`.
Nekushandisa huwandu hwakawanda hwemabasa akapihwa nePandas, iwe unenge wakashongedzerwa zvakakwana kubata akasiyana siyana data manipulation mabasa uye kuburitsa ruzivo rwakakosha kubva kumaseti ako.
