Pandas ɗakin karatu ne na Python wanda ake amfani da shi sosai don sarrafa bayanai da bincike, kuma iloc aiki ne mai mahimmanci a cikin ɗakin karatu wanda ke ba masu amfani damar zaɓar da sarrafa bayanai ta hanyar ƙididdige ƙididdiga. Wannan na iya zama da amfani musamman lokacin aiki tare da manyan bayanan bayanai. A cikin wannan labarin, za mu bincika da amfani pandas a cikin yanayi daban-daban kuma bayyana yadda aikin ke aiki mataki-mataki don taimaka muku fahimtar mahimmancinsa da yuwuwar aikace-aikacensa a cikin nazarin bayanai.
pandas iloc: Maganin Matsalar gama gari
Kalubalen gama gari da masu nazarin bayanai ke fuskanta shi ne yadda za su iya zaɓar da kuma tantance takamaiman sassan bayanansu yadda ya kamata. Abun DataFrame a cikin pandas yana ba da kyawawan hanyoyi da yawa don magance waɗannan ƙalubalen, kuma ɗayan mafi dacewa da ayyuka masu ƙarfi shine iloc mai ma'ana. Yana bawa masu amfani damar samun dama ga layuka da ginshiƙan DataFrame bisa tushen ƙididdigewa.
Bari mu fara da tattauna bayanin mataki-mataki na yadda ake amfani da iloc a cikin yanayin nazarin bayanai mai amfani.
Bayanin mataki-mataki na Pandas iloc
Amfani da pandas iloc abu ne mai sauƙi kuma mai fahimta. A ce muna da DataFrame mai zuwa:
import pandas as pd
data = {'Name': ['Alice', 'Bob', 'Cathy', 'David'],
'Age': [25, 29, 21, 35],
'City': ['New York', 'San Francisco', 'Los Angeles', 'Boston']}
df = pd.DataFrame(data)
Our DataFrame yana da layuka 4 da ginshiƙai 3. Don amfani da iloc, kuna buƙatar samar da fihirisa don layuka da ginshiƙan da kuke son shiga. Ga wasu misalai:
1. Samun dama ga takamaiman jere da shafi:
# Access row 2 (index 1) and column 'Name' (index 0) selected_data = df.iloc[1, 0] print(selected_data) # Output: Bob
2. Samun dama ga kewayon layuka da ginshiƙai:
# Access rows 1 to 3 (indexes 0 and 1) and columns 'Name' and 'Age' (indexes 0 and 1) selected_data = df.iloc[0:2, 0:2] print(selected_data) # Output: # Name Age # 0 Alice 25 # 1 Bob 29
3. Shiga takamaiman layuka da ginshiƙai:
# Access rows 1 and 4 (indexes 0 and 3) and columns 'Name' and 'City' (indexes 0 and 2) selected_data = df.iloc[[0, 3], [0, 2]] print(selected_data) # Output: # Name City # 0 Alice New York # 3 David Boston
Dakunan karatu da Dogara
don amfani da pandas, kuna buƙatar shigar da ɗakin karatu na pandas, da kuma duk wani ɗakin karatu da pandas ya dogara da su, kamar NumPy. Kuna iya shigar da su ta hanyar pip ko conda:
pip install pandas numpy
or
conda install pandas numpy
Da zarar an shigar da ɗakunan karatu, za ku iya fara amfani da pandas da iloc a cikin yanayin Python kamar yadda aka nuna a cikin misalan da ke sama.
Sauran Ayyuka masu alaƙa da Hanyoyin Fihirisa
Ban da iloc, pandas yana ba da wasu ayyuka da yawa da hanyoyin ƙididdigewa waɗanda zasu iya zama masu amfani a yanayi daban-daban. Wasu daga cikin manyan su ne:
- wuri: Wannan firikwensin yana bawa masu amfani damar samun dama ga layuka da ginshiƙai bisa tushen alamar alamar, maimakon maƙasudin tushen lamba kamar iloc.
- a: Ana amfani da shi don samun dama ga ƙima guda ɗaya bisa tushen alamar alamar.
- ina: Kama da 'at', amma don ƙididdigar tushen lamba. Ana amfani da shi don samun damar ƙima guda ɗaya bisa tushen ƙima.
Bincika waɗannan ayyuka da fahimtar yadda za a iya amfani da su a hade tare da iloc zai ƙarfafa ikon ku na yin hadadden sarrafa bayanai ta amfani da pandas.
