Data Cleaning With Python
We will now lead you through the following set of tasks, using Pandas and NumPy.
We will now lead you through the following set of tasks, using Pandas and NumPy.
Importing Libraries
Importing Libraries
Let’s get Pandas and NumPy up and running on your Python script.
INPUT:
import pandas as pd
import numpy as np
Let’s get Pandas and NumPy up and running on your Python script.
INPUT:
import pandas as pd import numpy as np
Input Customer Feedback Dataset
Input Customer Feedback Dataset
we ask our libraries to read a feedback dataset
INPUT:
data = pd.read_csv('feedback.csv')
we ask our libraries to read a feedback dataset
INPUT:
data = pd.read_csv('feedback.csv')
Locate Missing Data
Locate Missing Data
we are going to use a secret Python hack known as ‘isnull function’ to discover our data
we are going to use a secret Python hack known as ‘isnull function’ to discover our data
Check for Duplicates
Check for Duplicates
we are going to use a secret Python hack known as ‘isnull function’ to discover our data
we are going to use a secret Python hack known as ‘isnull function’ to discover our data
Detect Outliers
Detect Outliers
Outliers are numerical values that lie significantly outside of the statistical norm.
Outliers are numerical values that lie significantly outside of the statistical norm.
Detect Outliers
Detect Outliers
Outliers are numerical values that lie significantly outside of the statistical norm
data['Rating'].describe()
Outliers are numerical values that lie significantly outside of the statistical norm
data['Rating'].describe()
Normalize Casing
Normalize Casing
we are going to standardize (lowercase) all review titles so as not to confuse our algorithms,
we are going to standardize (lowercase) all review titles so as not to confuse our algorithms,
phone 9411778145
phone 9411778145
"Learn the skills in Data Science and analytics" FOR BUIDING
YOUR
CAREER IN ANALYTICS & data Science
"Learn the skills in Data Science and analytics"
FOR BUIDING
YOUR
CAREER IN ANALYTICS & data Science