Practical Python Data Science Techniques

Exploring Your Data 4 lectures 39:23 The Course Overview This video provides an overview of the entire course. Loading Data into Python This video discusses how to access data from local files in different formats. The aim of the video is to understand the most common file formats used to exchange data, and how Python makes it easy to access these formats.

• Read local files using Python
• Access common data formats like CSV and JSON
• Serialize binary data using the pickle module

A New Data Set – Exploratory Analysis This video introduces the notion of exploratory analysis and outlines some of the common steps that an analyst needs to take when dealing with a new data set.

• Compute summary statistics on a new data set
• Understand the distribution of different values
• Bucketing and plotting the data

Getting Data in the Right Shape – Preprocessing and Cleaning This video discusses the most common steps that are required to get the data in the right shape, including preprocessing and cleaning.

• Identify data that need cleaning and preprocessing
• Deal with duplicates and missing data
• Transform the data

Exploring Your Data 4 lectures 39:23 The Course Overview This video provides an overview of the entire course. Loading Data into Python This video discusses how to access data from local files in different formats. The aim of the video is to understand the most common file formats used to exchange data, and how Python makes it easy to access these formats.

• Read local files using Python
• Access common data formats like CSV and JSON
• Serialize binary data using the pickle module

A New Data Set – Exploratory Analysis This video introduces the notion of exploratory analysis and outlines some of the common steps that an analyst needs to take when dealing with a new data set.

• Compute summary statistics on a new data set
• Understand the distribution of different values
• Bucketing and plotting the data

Getting Data in the Right Shape – Preprocessing and Cleaning This video discusses the most common steps that are required to get the data in the right shape, including preprocessing and cleaning.

• Identify data that need cleaning and preprocessing
• Deal with duplicates and missing data
• Transform the data

The Course Overview This video provides an overview of the entire course. The Course Overview This video provides an overview of the entire course. The Course Overview This video provides an overview of the entire course. The Course Overview This video provides an overview of the entire course. This video provides an overview of the entire course. This video provides an overview of the entire course. Loading Data into Python This video discusses how to access data from local files in different formats. The aim of the video is to understand the most common file formats used to exchange data, and how Python makes it easy to access these formats.

• Read local files using Python
• Access common data formats like CSV and JSON
• Serialize binary data using the pickle module

Loading Data into Python This video discusses how to access data from local files in different formats. The aim of the video is to understand the most common file formats used to exchange data, and how Python makes it easy to access these formats.

• Read local files using Python
• Access common data formats like CSV and JSON
• Serialize binary data using the pickle module

Loading Data into Python This video discusses how to access data from local files in different formats. The aim of the video is to understand the most common file formats used to exchange data, and how Python makes it easy to access these formats.

• Read local files using Python
• Access common data formats like CSV and JSON
• Serialize binary data using the pickle module

Loading Data into Python This video discusses how to access data from local files in different formats. The aim of the video is to understand the most common file formats used to exchange data, and how Python makes it easy to access these formats.

• Read local files using Python
• Access common data formats like CSV and JSON
• Serialize binary data using the pickle module

This video discusses how to access data from local files in different formats. The aim of the video is to understand the most common file formats used to exchange data, and how Python makes it easy to access these formats.

• Read local files using Python
• Access common data formats like CSV and JSON
• Serialize binary data using the pickle module

This video discusses how to access data from local files in different formats. The aim of the video is to understand the most common file formats used to exchange data, and how Python makes it easy to access these formats.

• Read local files using Python
• Access common data formats like CSV and JSON
• Serialize binary data using the pickle module

A New Data Set – Exploratory Analysis This video introduces the notion of exploratory analysis and outlines some of the common steps that an analyst needs to take when dealing with a new data set.

• Compute summary statistics on a new data set
• Understand the distribution of different values
• Bucketing and plotting the data

A New Data Set – Exploratory Analysis This video introduces the notion of exploratory analysis and outlines some of the common steps that an analyst needs to take when dealing with a new data set.

• Compute summary statistics on a new data set
• Understand the distribution of different values
• Bucketing and plotting the data

A New Data Set – Exploratory Analysis This video introduces the notion of exploratory analysis and outlines some of the common steps that an analyst needs to take when dealing with a new data set.

• Compute summary statistics on a new data set
• Understand the distribution of different values
• Bucketing and plotting the data

A New Data Set – Exploratory Analysis This video introduces the notion of exploratory analysis and outlines some of the common steps that an analyst needs to take when dealing with a new data set.

• Compute summary statistics on a new data set
• Understand the distribution of different values
• Bucketing and plotting the data

This video introduces the notion of exploratory analysis and outlines some of the common steps that an analyst needs to take when dealing with a new data set.

• Compute summary statistics on a new data set
• Understand the distribution of different values
• Bucketing and plotting the data

This video introduces the notion of exploratory analysis and outlines some of the common steps that an analyst needs to take when dealing with a new data set.

• Compute summary statistics on a new data set
• Understand the distribution of different values
• Bucketing and plotting the data

Getting Data in the Right Shape – Preprocessing and Cleaning This video discusses the most common steps that are required to get the data in the right shape, including preprocessing and cleaning.

• Identify data that need cleaning and preprocessing
• Deal with duplicates and missing data
• Transform the data

Getting Data in the Right Shape – Preprocessing and Cleaning This video discusses the most common steps that are required to get the data in the right shape, including preprocessing and cleaning.

• Identify data that need cleaning and preprocessing
• Deal with duplicates and missing data
• Transform the data

Getting Data in the Right Shape – Preprocessing and Cleaning This video discusses the most common steps that are required to get the data in the right shape, including preprocessing and cleaning.

• Identify data that need cleaning and preprocessing
• Deal with duplicates and missing data
• Transform the data

Getting Data in the Right Shape – Preprocessing and Cleaning This video discusses the most common steps that are required to get the data in the right shape, including preprocessing and cleaning.

• Identify data that need cleaning and preprocessing
• Deal with duplicates and missing data
• Transform the data

This video discusses the most common steps that are required to get the data in the right shape, including preprocessing and cleaning.

• Identify data that need cleaning and preprocessing
• Deal with duplicates and missing data
• Transform the data

This video discusses the most common steps that are required to get the data in the right shape, including preprocessing and cleaning.

• Identify data that need cleaning and preprocessing
• Deal with duplicates and missing data
• Transform the data

Dealing with Text 4 lectures 40:07 Tokenization – From Documents to Words This video discusses the process of breaking a string down into individual tokens or phrases, including text data from different domains (For example, social media versus general English).

• Identify tokens from text
• Deal with text from different domains
• Identify phrases to capture more complex concepts

Stop-Words and Punctuation Removal This video discusses the process of removing stop-words (unimportant words) and punctuation from a list of tokens.

• Define stop-words and unimportant words
• Remove stop-words and punctuation tokens
• Deal with Unicode symbols

Text Normalization This video introduces the most common steps for text normalization that is the process of transforming a token into its canonical form.

• Transform tokens using case normalization
• Transform tokens using stemming and normalization
• Transform tokens using synonym mapping

Calculating Word Frequencies This video discusses how to calculate word frequencies within documents and across a whole collection, and how to read.

• Find the most common word or phrases in a document
• Find the most common word or phrases in a collection
• Understand the role of word frequencies in text analytics.

Dealing with Text. 4 lectures 40:07 Tokenization – From Documents to Words This video discusses the process of breaking a string down into individual tokens or phrases, including text data from different domains (For example, social media versus general English).

• Identify tokens from text
• Deal with text from different domains
• Identify phrases to capture more complex concepts

Stop-Words and Punctuation Removal This video discusses the process of removing stop-words (unimportant words) and punctuation from a list of tokens.

• Define stop-words and unimportant words
• Remove stop-words and punctuation tokens
• Deal with Unicode symbols

Text Normalization This video introduces the most common steps for text normalization that is the process of transforming a token into its canonical form.

• Transform tokens using case normalization
• Transform tokens using stemming and normalization
• Transform tokens using synonym mapping

Calculating Word Frequencies This video discusses how to calculate word frequencies within documents and across a whole collection, and how to read.

• Find the most common word or phrases in a document
• Find the most common word or phrases in a collection
• Understand the role of word frequencies in text analytics.

Tokenization – From Documents to Words This video discusses the process of breaking a string down into individual tokens or phrases, including text data from different domains (For example, social media versus general English).

• Identify tokens from text
• Deal with text from different domains
• Identify phrases to capture more complex concepts

Tokenization – From Documents to Words This video discusses the process of breaking a string down into individual tokens or phrases, including text data from different domains (For example, social media versus general English).

• Identify tokens from text
• Deal with text from different domains
• Identify phrases to capture more complex concepts

Tokenization – From Documents to Words This video discusses the process of breaking a string down into individual tokens or phrases, including text data from different domains (For example, social media versus general English).

• Identify tokens from text
• Deal with text from different domains
• Identify phrases to capture more complex concepts

Tokenization – From Documents to Words This video discusses the process of breaking a string down into individual tokens or phrases, including text data from different domains (For example, social media versus general English).

• Identify tokens from text
• Deal with text from different domains
• Identify phrases to capture more complex concepts

This video discusses the process of breaking a string down into individual tokens or phrases, including text data from different domains (For example, social media versus general English).

• Identify tokens from text
• Deal with text from different domains
• Identify phrases to capture more complex concepts

This video discusses the process of breaking a string down into individual tokens or phrases, including text data from different domains (For example, social media versus general English).

• Identify tokens from text
• Deal with text from different domains
• Identify phrases to capture more complex concepts

Stop-Words and Punctuation Removal This video discusses the process of removing stop-words (unimportant words) and punctuation from a list of tokens.

• Define stop-words and unimportant words
• Remove stop-words and punctuation tokens
• Deal with Unicode symbols

Stop-Words and Punctuation Removal This video discusses the process of removing stop-words (unimportant words) and punctuation from a list of tokens Regression Analysis – Predicting a Quantity This video introduces regression analysis as the problem of predicting a quantity, or a continuous variable, using scikit-learn.

• Shape a problem as regression...