Pandas iraibhurari ine simba yePython yekuongorora data uye kunyengedza, inoshandiswa zvakanyanya munzvimbo dzakasiyana siyana, kusanganisira nyika yemafashoni. Kushandisa Pandas, nyanzvi dzefashoni uye vanogadzira vanogona kuona mafambiro, mapatani, uye ruzivo nekuongorora dataset ine chekuita neindasitiri yemafashoni. Muchinyorwa chino, isu tichanyura mune ane simba Pandas mabasa, zvinoreva uye sum, uye kushandiswa kwavo mukuongorora kwemafashoni data.
Aya mabasa anogona kubatsira zvakanyanya mukutsvaga ruzivo rwakakosha nezvezvinhu zvefashoni sekutengesa, mafambiro emitengo, chiyero chechigadzirwa, nezvimwe. Nekuverengera zvinoreva uye huwandu hweakasiyana hunhu, tinogona kutora maonero akakosha kuita sarudzo dzine ruzivo nezve masitaera nemafashoni.
Mhinduro kudambudziko
Kuratidza kushandiswa kwepandas zvinoreva uye sum mabasa, ngatifungei isu tine dhatabheti rine ruzivo rwezvakasiyana zvinhu zvefashoni senge maitiro avo, mavara, mutengo, uye chiyero. Tichapinza iyi dataset mupandas DataFrame totanga ongororo yedu tichishandisa zvinoreva uye sum mabasa.
import pandas as pd
# Read data from a CSV file and load it into a DataFrame
data = pd.read_csv('fashion_items.csv')
# Calculate mean and sum of the price column
mean_price = data['price'].mean()
sum_price = data['price'].sum()
print('Mean price:', mean_price)
print('Total price:', sum_price)
Nhanho-nhanho tsananguro yekodhi
- Kutanga, isu tinopinza raibhurari yepandas ine alias 'pd'.
- Tevere, tinoverenga data kubva kufaira reCSV rakanzi 'fashion_items.csv' uye toiisa muDataFrame inonzi 'data' tichishandisa pd.read_csv basa. Iyo dataset ine ruzivo nezve akasiyana fashoni zvinhu.
- Zvadaro, isu tinoverenga mutengo unoreva wezvinhu zvese zvemafashoni tichishandisa zvinoreva () basa rinoiswa kune 'mutengo' column yeDataFrame. Ukoshi uhwu hunochengetwa mune vhezheni inonzi 'mean_price'.
- Saizvozvo, isu tinoverenga mutengo wakakwana wezvinhu zvese zvefashoni nekudaidza iyo sum () basa pane 'mutengo' column. Ukoshi uhwu hunochengetwa mune vhezheni inonzi 'sum_price'.
- Pakupedzisira, tinodhinda zvakaverengerwa zvinoreva uye mitengo yakazara yezvinhu zvefashoni.
Maraibhurari ane hukama uye mabasa muPandas
Kune kuwanda kwemaraibhurari uye mabasa anoenderana nekushandiswa kwepandas yekuongorora data muindasitiri yemafashoni. Zvimwe zveizvi zvinobatsira mabasa kunze zvinoreva uye sum dzinosanganisira:
Pandas groupby basa
The groupby basa rinonyanya kubatsira pakuunganidza data zvichienderana nemakoramu chaiwo. Semuyenzaniso, kana tichida kuongorora zvinorehwa uye mutengo wakakwana wezvinhu zvefashoni zvemhando yega yega iripo mune yedu dataset.
# Group data by style and calculate mean and sum of the price
grouped_data = data.groupby('style')['price'].agg(['mean', 'sum'])
print(grouped_data)
Pandas inobatanidza basa
The famba basa rinotibvumira kusanganisa maviri DataFrames zvichienderana nekoramu yakafanana. Semuenzaniso, ngatiti isu tine dataset yakaparadzana ine ruzivo nezve kufarirwa kwemaitiro ega ega. Nekubatanidza ese ari maviri DataFrames, tinogona kushandura ruzivo urwu kuita ruzivo rwakakosha.
# Import data related to style popularity
style_popularity_data = pd.read_csv('style_popularity.csv')
# Merge the original data and style_popularity_data based on the 'style' column
merged_data = pd.merge(data, style_popularity_data, on='style')
print(merged_data.head())
Nekunzwisisa nekuita aya mabasa ane simba mukati mePandas raibhurari, nyanzvi dzefashoni nevagadziri vanogona kuita sarudzo dzine ruzivo uye kuongorora zvichangobva kuitika uye masitayipi zviri nyore.
