An warware: pytorch mirgina taga

Duniyar nazarin bayanai galibi tana buƙatar yin aiki tare da bayanan jerin lokaci, kuma wata dabara ta gama gari da ake amfani da ita wajen sarrafa irin waɗannan bayanan tana amfani da manufar mirgina taga. Taga mai birgima, wani lokacin ana kiranta da taga mai motsi ko taga mai zamewa, hanya ce da ke ba mu damar raba saitin bayanan mu zuwa ƙananan guntu, sarrafa su, da samun fa'ida mai fa'ida daga jerin abubuwan da aka haifar. Ana amfani da wannan fasaha mai ƙarfi sosai a fannin kuɗi, hasashen hasashen, da kuma bincike na zamani, yana mai da shi fasaha mai mahimmanci don samun cikin akwatin kayan aikin bincike. A cikin wannan labarin, za mu bincika manufar taga mai birgima, magance matsala, warware matsalarta zuwa matakai masu sauƙin fahimta, da tattauna dakunan karatu da ayyukan Python masu alaƙa waɗanda za su iya sauƙaƙa rayuwarmu.

Bayanin Matsala

Bari mu ɗauka muna da tsarin bayanan lokaci wanda ya ƙunshi alkalumman tallace-tallace na yau da kullun na kantin sayar da kayayyaki na shekara guda. Ayyukanmu shine bincika wannan saitin bayanai da ƙididdige matsakaicin tallace-tallace na kwanaki 7 don daidaita abubuwan da ba su dace ba, gano abubuwan da ke faruwa, da jagoranci yanke shawarar kasuwanci. Za mu yi amfani da Python, sanannen kuma yaren shirye-shirye da ake amfani da shi sosai don nazarin bayanai.

Hanyar Magani

Don warware matsalar taga mai juyi, za mu bi waɗannan matakan:

1. Shigo da dakunan karatu da suka dace
2. Loda saitin bayanai
3. Ƙirƙiri taga mai jujjuyawa
4. Yi lissafin matsakaicin motsi na kwanaki 7
5. Yi tunanin sakamakon

Bari mu fara da shigo da dakunan karatu da ake buƙata da loda saitin bayanai.

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

# Load dataset (Assuming the dataset is a CSV file)
data = pd.read_csv('sales_data.csv')

# Preview the dataset
print(data.head())

Bayan mun loda saitin bayanai, yanzu mun ci gaba da ƙirƙirar taga mai jujjuyawa.

Ƙirƙirar Tagar Bidiyo

Mu juya zuwa ga masu iko Panda ɗakin karatu don ƙirƙirar taga mai jujjuyawa ta amfani da rolling() aiki. Tagan mai juyi zai sami girman kwanaki 7, kamar yadda muke son ƙididdige matsakaicin motsi na kwanaki 7.

# Create a rolling window of 7 days
rolling_window = data['sales'].rolling(window=7)

Yanzu da muke da taga mai juyi, za mu iya ƙididdige matsakaicin motsi na kwanaki 7.

Ana ƙididdige Matsakaicin Motsi na Kwanaki 7

Don nemo matsakaita na tallace-tallace na kwanaki 7, muna kiran kawai mean() aiki akan abin taga mu na mirgina. Sa'an nan kuma mu ƙara wannan sabon matsakaicin motsi a matsayin sabon shafi a cikin bayanan mu.

# Calculate the moving average
data['7_day_avg'] = rolling_window.mean()

# Preview the updated dataset
print(data.head(10))

A ƙarshe, bari mu hango sakamakonmu don ƙarin fahimtar abubuwan da ke cikin bayananmu.

Sakamako Mai Kallon gani

Za mu yi amfani da mashahuri matplotlib ɗakin karatu don ƙirƙirar ginshiƙi mai sauƙi wanda ke nuna duka bayanan tallace-tallace na yau da kullun da matsakaicin motsi na kwanaki 7 da aka ƙididdige.

# Plot the daily sales data
plt.plot(data['sales'], label='Daily Sales')

# Plot the 7-day moving average
plt.plot(data['7_day_avg'], label='7-Day Moving Average', color='red')

# Add labels and legend
plt.xlabel('Days')
plt.ylabel('Sales')
plt.title('Daily Sales and 7-Day Moving Average')
plt.legend()

# Display the plot
plt.show()

Taswirar da aka ƙirƙira yana nuna bayanan tallace-tallace na yau da kullun tare da matsakaicin motsi na kwanaki 7, yana sauƙaƙa mana gano abubuwan da ke faruwa da abubuwan da ba su da kyau.

A ƙarshe, ana amfani da taga mai birgima sosai a cikin nazarin bayanai, musamman jerin lokaci, don ikonsa na bayyana ɓoyayyun alamu da abubuwan da ke faruwa a cikin manyan bayanan bayanai. Haɗin Python, Pandas, da Matplotlib yana sauƙaƙe tsarin ƙididdige matsakaicin motsi da hangen nesa, yana mai da shi batun kusanci ga masu farawa da masana a fagen.