Falanqaynta Isdhexgalka (Correlation Analysis) ee Python

Falanqaynta isdhexgalka waa hab lagu cabbiro xidhiidhka ka dhexeeya laba doorsoome. Waxay muujinaysaa sida doorsoome mid u saameeyo doorsoomaha kale. Python, waxaan u isticmaali karnaa maktabado sida NumPy iyo SciPy si aan u samayno falanqayntan.

Tusaale:

Aynu eegno sida loo xisaabiyo isdhexgalka u dhexeeya laba taxane oo xog ah.

import numpy as np
from scipy.stats import pearsonr

# Xogta
x = np.array([1, 2, 3, 4, 5])
y = np.array([2, 4, 5, 4, 5])

# Xisaabi isdhexgalka
correlation, p_value = pearsonr(x, y)

print(f"Isku xidhka Pearson: {correlation}")
print(f"Qiimaha P: {p_value}")

Sharaxaada:

• Waxaan soo dejinay maktabadaha NumPy iyo pearsonr oo ka socda SciPy.
• Waxaan abuurnay laba taxane oo xog ah, x iyo y.
• Waxaan u isticmaalnay shaqada pearsonr() si aan u xisaabino isdhexgalka Pearson iyo qiimaha P.
• Waxaan daabacnay natiijada.

Fahamka Natiijooyinka

Isku xidhka Pearson wuxuu cabbiraa xoogga iyo jihada xidhiidhka toosan ee u dhexeeya laba doorsoome:

• 1: Xidhiidh toosan oo dhammaystiran.
• -1: Xidhiidh taban oo dhammaystiran.
• 0: Ma jiro xidhiidh.

Qiimaha P wuxuu muujinayaa muhiimadda tirakoob ee isdhexgalka. Qiime hooseeya (tusaale, < 0.05) wuxuu tilmaamayaa in isdhexgalku yahay mid muhiim ah.

Isticmaalka Xogta Dhabta ah

Aynu isticmaalno xogta dhabta ah ee ka timaadda faylka CSV.

import pandas as pd
from scipy.stats import pearsonr

# Soo dejiso xogta
data = pd.read_csv('xogta.csv')

# Xisaabi isdhexgalka u dhexeeya laba column
correlation, p_value = pearsonr(data['Column1'], data['Column2'])

print(f"Isku xidhka Pearson: {correlation}")
print(f"Qiimaha P: {p_value}")

Xusuusnow inaad ku beddesho xogta.csv magaca saxda ah ee faylkaaga iyo Column1 iyo Column2 magacyada saxda ah ee columns-kaaga.