Alimr.dev

Introduction

We briefly introduced some of the most common classes and methods in the Introduction tutorial. In this tutorial we go through some more! Pandas provides plenty of methods to obtain basic information about the data. The following are some of the common methods and objects:

• index
• column
• describe
• info
• dtypes
• shape
• size

# Load a sample data
import pandas as pd
dataPath = 'https://raw.githubusercontent.com/alineu/pyDataScintist-Notebooks/main/data/'
df = pd.read_csv(dataPath+'car_data.csv')
df.head()

	symboling	normalized-losses	make	fuel-type	aspiration	num-of-doors	body-style	drive-wheels	engine-location	wheel-base	...	engine-size	fuel-system	bore	stroke	compression-ratio	horsepower	peak-rpm	city-mpg	highway-mpg	price
0	3	?	alfa-romero	gas	std	two	convertible	rwd	front	88.6	...	130	mpfi	3.47	2.68	9.0	111	5000	21	27.0	13495
1	3	?	alfa-romero	gas	std	two	convertible	rwd	front	88.6	...	130	mpfi	3.47	2.68	9.0	111	5000	21	27.0	16500
2	1	?	alfa-romero	gas	std	two	hatchback	rwd	front	94.5	...	152	mpfi	2.68	3.47	9.0	154	5000	19	26.0	16500
3	2	164	audi	gas	std	four	sedan	fwd	front	99.8	...	109	mpfi	3.19	3.4	10.0	102	5500	24	30.0	13950
4	2	164	audi	gas	std	four	sedan	4wd	front	99.4	...	136	mpfi	3.19	3.4	8.0	115	5500	18	22.0	17450

5 rows × 26 columns

index: Stores the Index labels for all objects

df.index

RangeIndex(start=0, stop=205, step=1)

columns: Stores the column labels for pandas DataFrames

df.columns

Index(['symboling', 'normalized-losses', 'make', 'fuel-type', 'aspiration',
       'num-of-doors', 'body-style', 'drive-wheels', 'engine-location',
       'wheel-base', 'length', 'width', 'height', 'curb-weight', 'engine-type',
       'num-of-cylinders', 'engine-size', 'fuel-system', 'bore', 'stroke',
       'compression-ratio', 'horsepower', 'peak-rpm', 'city-mpg',
       'highway-mpg', 'price'],
      dtype='object')

describe: Provides a summary of descriptive statistics, excluding NaN values, for all columns with numerical data types.

df.describe()

	symboling	wheel-base	length	width	height	curb-weight	engine-size	compression-ratio	city-mpg	highway-mpg
count	205.000000	202.000000	205.000000	205.000000	205.000000	203.000000	205.000000	205.000000	205.000000	200.000000
mean	0.834146	98.821287	174.049268	65.907805	53.724878	2558.211823	126.907317	10.142537	25.219512	30.695000
std	1.245307	5.982678	12.337289	2.145204	2.443522	520.943508	41.642693	3.972040	6.542142	6.937769
min	-2.000000	86.600000	141.100000	60.300000	47.800000	1488.000000	61.000000	7.000000	13.000000	16.000000
25%	0.000000	94.500000	166.300000	64.100000	52.000000	2157.000000	97.000000	8.600000	19.000000	25.000000
50%	1.000000	97.000000	173.200000	65.500000	54.100000	2414.000000	120.000000	9.000000	24.000000	30.000000
75%	2.000000	102.300000	183.100000	66.900000	55.500000	2943.500000	141.000000	9.400000	30.000000	34.000000
max	3.000000	120.900000	208.100000	72.300000	59.800000	4066.000000	326.000000	23.000000	49.000000	54.000000

info: Shows information about a DataFrame including the index, column names, data type, non-null values count, and memory used by the DataFrame

df.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 205 entries, 0 to 204
Data columns (total 26 columns):
 #   Column             Non-Null Count  Dtype  
---  ------             --------------  -----  
 0   symboling          205 non-null    int64  
 1   normalized-losses  205 non-null    object 
 2   make               205 non-null    object 
 3   fuel-type          205 non-null    object 
 4   aspiration         204 non-null    object 
 5   num-of-doors       205 non-null    object 
 6   body-style         204 non-null    object 
 7   drive-wheels       205 non-null    object 
 8   engine-location    205 non-null    object 
 9   wheel-base         202 non-null    float64
 10  length             205 non-null    float64
 11  width              205 non-null    float64
 12  height             205 non-null    float64
 13  curb-weight        203 non-null    float64
 14  engine-type        205 non-null    object 
 15  num-of-cylinders   205 non-null    object 
 16  engine-size        205 non-null    int64  
 17  fuel-system        205 non-null    object 
 18  bore               205 non-null    object 
 19  stroke             205 non-null    object 
 20  compression-ratio  205 non-null    float64
 21  horsepower         205 non-null    object 
 22  peak-rpm           203 non-null    object 
 23  city-mpg           205 non-null    int64  
 24  highway-mpg        200 non-null    float64
 25  price              205 non-null    object 
dtypes: float64(7), int64(3), object(16)
memory usage: 41.8+ KB

dtypes: Shows the data type of each column

df.dtypes

symboling              int64
normalized-losses     object
make                  object
fuel-type             object
aspiration            object
num-of-doors          object
body-style            object
drive-wheels          object
engine-location       object
wheel-base           float64
length               float64
width                float64
height               float64
curb-weight          float64
engine-type           object
num-of-cylinders      object
engine-size            int64
fuel-system           object
bore                  object
stroke                object
compression-ratio    float64
horsepower            object
peak-rpm              object
city-mpg               int64
highway-mpg          float64
price                 object
dtype: object

shape: Shows the number of rows and columns of a pandas object

df.shape

(205, 26)

size: Returns the number of rows in a pandas Series or the number of rows times the number of columns of a DataFrame

df.shape

5330