Final Exam: Dynamic Data Handling with Python
Python 3.6+ | Intermediate
- 1 Video | 32s
- Includes Assessment
- Earns a Badge
Final Exam: Dynamic Data Handling with Python will test your knowledge and application of the topics presented throughout the Dynamic Data Handling with Python track of the Skillsoft Aspire Pythonista to Python Master Journey.
WHAT YOU WILL LEARN
insert data into viewsperform various import and export operations on CSV, TSV, and TXT files.perform various grouping operations on the data in a tableperform various update and replace operations on petl data tables by defining functions to perform transformationsinstall petl and create a basic petl data table out of toy datacreate a table in SQLite and read it into petl using SQLAlchemy and SQLite3identify the different options available to stream large volumes of data in an HTTP responsesubmit data to a remote server using a POST request with HTTPXmap fields in a petl table to transformation based on functionscreate and invoke stored proceduresuse the HTTPX AsynClient to download a set of files asynchronouslycreate and use a SQL primary key constraint with autoincrementget data from MS Excel and perform basic operations on the datainsert and edit columns and rows in petl data tablesuse the fetchmany() function to retrieve the output of a select queryrecognize when a redirect has taken place upon submitting an HTTP requestimplement insert and delete operationsrecall the types of exceptions that can be encountered when sending and processing requests with HTTPXinstall SQLAlchemy and connect to MySQLquery data using object relational mappingconfigure an httpx.Cookies instance to send a collection of properties to a remote serverimplement check constraintsread in data from the serialized pickle and XML file formatscreate tables using object relational mappingwork with transaction abortsdefine and submit a POST request containing JSON and binary datainsert rows into a tableread JSON data, perform various operations, and export it to a persistent formatlimit the amount of time your app spends waiting to get served a response to an HTTP request using timeoutsidentify when a redirect has taken place upon submitting an HTTP request
create a table and insert rows into itrecognize the types of exceptions that can be encountered when sending and processing requests with HTTPXinstall the latest available version of HTTPX on your systemexplore different ways to use logical operators for querying dataimplement an httpx.Cookies instance to send a collection of properties to a remote serveruse triggers to automate operationsimplement slicing, dicing, and merging operations on petl data tablesuse the aggregate function to calculate aggregate statistics for a field in a tableperform SQL like equi-joins on petl data tablesperform insert and delete operationscreate SQL indexes on tablesadd a foreign key constraint between tablesretrieve information about a remote resource using a HEAD requestimplement split operations on data stored within petl tablesuse the facet petl function to define filters on specific fields in a tablerecognize the messages conveyed in the different status codes sent in an HTTP responsedownload a set of files sequentially using HTTPXimplement specialized types of joins such as anti joins and cross joinsdrop a table, recreate it, and insert rows into itexecute alter operations to add constraints and indices to tablesanalyze the common and distinct values in two tables using various petl functionsinsert and edit rows and columns in petl data tablesperform joins based on overlapping intervals rather than absolute valuesautomate operations using triggersinstall SQLAlchemy and connect to MySQLuse slicing, dicing, and merging operations on petl data tablesuse an httpx.Cookies instance to send a collection of properties to a remote serversubmit HTTP GET requests with one or more parameters using HTTPXmake use of the rowreduce() function to reduce rows and compute aggregate statisticscalculate aggregate statistics for a field in a table using the aggregate function
IN THIS COURSE
1.Dynamic Data Handling with Python33sUP NEXT
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