Change language

Exploratory Data Analysis in Python | Set 1

To get a link to the csv file you are using, click here .

Loading libraries:

import numpy as np

import pandas as pd

import seaborn as sns

import matplotlib. pyplot as plt

 

 

from scipy.stats import trim_mean

Loading data:

data = pd.read_csv ( "state.csv" )

 
# Check the data type

print ( "Type:" , type (data), " " )

  
# Print top 10 posts

print ( " Head - " , data.head ( 10 ))

 
< code class = "comments"> # Print the last 10 entries

print ( "Tail -" , data.tail ( 10 ))

Output:

 Type: class ’pandas.core.frame.DataFrame’  Head -  State Population Murder.Rate Abbreviation 0 Alabama 4779736 5.7 AL 1 Alaska 710231 5.6 AK 2 Arizona 6392017 4.7 AZ 3 Arkansas 2915918 5.6 AR 4 California 37253956 4.4 CA 5 Colorado 5029196 2.8 CO 6 Connecticut 3574097 2.4 CT 7 Delaware 897934 5.8 DE 8 Florida 18801310 5.8 FL 9 Georgia 9687653 5.7 GA  Tail -  State Population Murder.Rate Abbreviation 40 South Dakota 814180 2.3 SD 41 Tennessee 6346105 5.7 TN 42 Texas 25145561 4.4 TX 43 Utah 2763885 2.3 UT 44 Vermont 625741 1.6 VT 45 Virginia 8001024 4.1 VA 46 Washington 6724540 2.5 WA 47 West Virginia 1852994 4. 0 WV 48 Wisconsin 5686986 2.9 WI 49 Wyoming 563626 2.7 WY 

Code # 1: Add Column to Data Frame

# Add a new derived data column

  

data [ ’PopulationInMillions’ ] = data [ ’Population’ ] / 1000000

 
# Changed data

print (data.head ( 5 ))

Output:

 State Population Murder.Rate Abbreviation PopulationInMillions 0 Alabama 4779736 5.7 AL 4.779736 1 Alaska 710231 5.6 AK 0.710231 2 Arizona 6392017 4.7 AZ 6.392017 3 Arkansas 2915918 5.6 AR 2.915918 4 California 37253956 4.4 CA 37.253956 
Code

: Data Description

data.describe ()

Output:

Code # 3: Data Information

data.info ()

Output:

 RangeIndex: 50 entries, 0 to 49 Data columns (tota l 4 columns): State 50 non-null object Population 50 non-null int64 Murder.Rate 50 non-null float64 Abbreviation 50 non-null object dtypes: float64 (1), int64 (1), object (2) memory usage: 1.6+ KB 

Code # 4: renaming a column header

# Rename the column header as it is
# has & # 39;. & # 39; in it, which will create
# problems when working with functions

  

data.rename (columns = { ’Murder.Rate’ : ’ MurderRate’ }, inplace = True )

 
# Let’s check the column headings

list (data)

Exit:

 [’State’,’ Population’, ’MurderRate’,’ Abbreviation’] 

Code # 5: Average calculation

Population_mean = data.Population.mean ()

print ( "Population Mean:" , Population_mean)

  

MurderRate_mean = data.MurderRate.mean ()

print ( "MurderRate Mean:" , MurderRate_mean)

Exit:

 Population Mean: 6162876.3 MurderRate Mean: 4.066 

Code # 6: Truncated Average

# Average after reset top and
# bottom 10% non-outliers

 

population_TM = trim_mean (data.Population, 0.1 )

print ( "Population trimmed mean:" , population_TM)

  

murder_TM = trim_mean (data.MurderRate, 0.1 )

print ( "MurderRate trimmed mean:" , murder_TM)

Output:

 Population trimmed mean: 4783697.125 Murde rRate trimmed mean: 3.9450000000000003 

Code # 7: weighted average

# here the kill rate is weighted according to
# public population

 

murderRate_WM = np.average (data.MurderRate, weights = data.Population)

print ( " Weighted MurderRate Mean: " , murderRate_WM)

Output:

 Weighted MurderRate Mean: 4.445833981123393 

Code # 8: Median

Population_median = data.Population.median ()

print ( "Population median:" , Population_median)

  

MurderRate_median = data .MurderRate.median ()

print ( "MurderRate median:" , MurderRate_median)

Output:

 Population median: 4436369.5 MurderRate median: 4.0 

Shop

Gifts for programmers

Learn programming in R: courses

$FREE
Gifts for programmers

Best Python online courses for 2022

$FREE
Gifts for programmers

Best laptop for Fortnite

$399+
Gifts for programmers

Best laptop for Excel

$
Gifts for programmers

Best laptop for Solidworks

$399+
Gifts for programmers

Best laptop for Roblox

$399+
Gifts for programmers

Best computer for crypto mining

$499+
Gifts for programmers

Best laptop for Sims 4

$

Latest questions

PythonStackOverflow

Common xlabel/ylabel for matplotlib subplots

1947 answers

PythonStackOverflow

Check if one list is a subset of another in Python

1173 answers

PythonStackOverflow

How to specify multiple return types using type-hints

1002 answers

PythonStackOverflow

Printing words vertically in Python

909 answers

PythonStackOverflow

Python Extract words from a given string

798 answers

PythonStackOverflow

Why do I get "Pickle - EOFError: Ran out of input" reading an empty file?

606 answers

PythonStackOverflow

Python os.path.join () method

384 answers

PythonStackOverflow

Flake8: Ignore specific warning for entire file

360 answers

News


Wiki

Python | How to copy data from one Excel sheet to another

Common xlabel/ylabel for matplotlib subplots

Check if one list is a subset of another in Python

How to specify multiple return types using type-hints

Printing words vertically in Python

Python Extract words from a given string

Cyclic redundancy check in Python

Finding mean, median, mode in Python without libraries

Python add suffix / add prefix to strings in a list

Why do I get "Pickle - EOFError: Ran out of input" reading an empty file?

Python - Move item to the end of the list

Python - Print list vertically