Mafashoni uye hurongwa zvingaite senyika mbiri dzakasiyana zvachose, asi kana zvasvika pakuongororwa kwedata uye kufanotaura kwemaitiro, vanogona kuuya pamwechete. Muchinyorwa chino, isu tichaongorora dambudziko rakajairwa rekuongororwa kwedata muindasitiri yemafashoni: kusiya mazuva chaiwo kubva papandas datetime data. Izvi zvinogona kunyanya kubatsira kana uchiongorora mapatani, maitiro, uye data rekutengesa. Tichapfuura nenhanho-ne-nhanho tsananguro yekodhi, uye tokurukura maraibhurari akasiyana-siyana uye mabasa ayo achatibatsira kuzadzisa chinangwa chedu.
Pandas uye Datetime muFashoni
Pandas iraibhurari yakakurumbira yePython inonyanya kushandiswa kuongorora data uye kunyengera. Munyika yemafashoni, inogona kushandiswa kusefa mukati mehuwandu hwe data kuona mafambiro, kuongorora zvinofarirwa nevatengi, uye kufanotaura mafambiro emangwana. Pandas inotsigira mashandiro enguva, ichitibvumira kushanda nemazuva uye nguva tisingashande.
Muzviitiko zvakawanda, zvinofanirwa kusiya mazuva chaiwo kana misimboti yemazuva kubva padataset yedu. Semuyenzaniso, tingangoda kusabatanidza kupera kwevhiki kana mazororo kuti titarise mazuva akakosha ekutengesa, seBlack Friday kana Cyber Monday.
Kunzwisisa Dambudziko
Ngatitii tine dhatabheti rine data rekutengesa zuva nezuva muCSV fomati, uye isu tinoda kuongorora ruzivo tisingasanganisire kupera kwevhiki. Kuti tiite izvi, tinotanga ne kupinza dhataset tichishandisa pandas, tobva tashandisa data kuti tibvise kupera kwevhiki.
Heino nhanho-ne-nhanho maitiro:
1. Kupinza maraibhurari anodiwa.
2. Rodha dataset.
3. Shandura koramu yemazuva kuti ive datetime fomati (kana isati yatove mune iyo fomati).
4. Sefa dataframe kuti usabatanidze kupera kwevhiki.
5. Ongorora data yakasefa.
Cherechedza: Iyi nzira inogona kushandiswa kune chero dataset uko zuva rakachengetwa mune yakaparadzana column.
# Step 1: Import the necessary libraries
import pandas as pd
from pandas.tseries.offsets import BDay
# Step 2: Load the dataset
data = pd.read_csv('sales_data.csv')
# Step 3: Convert the date column to datetime format
data['date'] = pd.to_datetime(data['date'])
# Step 4: Filter the dataframe to exclude weekends
filtered_data = data[data['date'].dt.dayofweek < 5]
# Step 5: Analyze the filtered data
print(filtered_data.head())
Kududzira Code
Muchivharo chekodhi chiri pamusoro, tinotanga nekuendesa kunze maraibhurari maviri akakosha: pandas uye BDay (zuva rebhizinesi) kubva pandas.tseries.offsets. Isu tinorodha iyo dataset tichishandisa iyo pandas basa read_csv, uye simbisa kuti koramu yemazuva iri mufomati yemazuva.
The dt.dayofweek hunhu hunodzosa zuva revhiki sechikamu (Muvhuro: 0, Svondo: 6). Kusefa kupera kwevhiki, tinongochengeta mitsara ine dayofweek kukosha isingasviki 5.
Pakupedzisira, isu tinoongorora iyo yakasefa data nekudhinda mitsetse mishoma yekutanga tichishandisa iyo musoro () basa.
Mamwe Mabasa uye Maraibhurari
Iyi nzira inogona kuwedzerwa kuti ibatanidze mamwe maitiro ekusefa kana kushanda nemisi yakasiyana-siyana. Mamwe maraibhurari anobatsira uye mabasa anogona kutsigira maitiro aya anosanganisira:
- numPy: Raibhurari yemakomputa enhamba muPython, iyo inogona kushandiswa kunyatsoita dhizaini uye mashandiro emasvomhu.
- DateTime: A module muPython's standard library iyo inotibatsira kushanda nemazuva uye nguva zviri nyore.
- date_range: Basa mukati me pandas rinotitendera kuti tigadzire huwandu hwemazuva zvinoenderana neakasiyana ma frequency marongero, senge mazuva ebhizinesi, mavhiki, kana mwedzi.
Nekushandisa maturusi aya uye matekiniki pamwe chete nepandas uye datetime manipulation, unogona kugadzira yakasimba yekuongorora data workflows inoenderana nezvinodiwa chaizvo zveindasitiri yemafashoni, senge kuona mafambiro, zvido zvevatengi, uye kuita kwekutengesa.
