Session 13: Instructor-led Live Training on Python Data Science NumPy and Pandas

Free of Cost – Specialist in Python (with Flask Towards Data Science) basic to advance by World Record Holder - Mr. Vimal Daga.

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[dipadityadas]

Session Summary:
✅We can do 3 types of operations like Query, Data Analysis, Data Analytics.
✅The dimensions of the dataset mean that the features of that dataset that it includes. When it contains more than one feature it is known as a multi-dimension dataset.
✅we can perform Query and Data Analysis on the historical data.
✅Yes, we can store it but we can't operate on it through column-wise.
✅In any function, there are multiple pre created statements that can be executed as and when required like numpy.array()

[Jai_]

#11/10/2020

I learnt about the
- Data and how the data will be stored ie. About the data structure.
- what are the things that can be done on data:- Query, Data Analysis, and Data Analystics.
- How datasets are used for data analysis
- About 1D, 2D and multi dimensional data.
- Numpy module and how it is powerfully used.
- On numpy library we have array as a function to do operations on data.
- array() such as sum(), max() and mean() we have seen.

Thank you sir for this wonderful session.

[manishverma]

Summary for session 13
The session was good and I learned so many new things like:
1. we can use dataset to do some query, analyis and analytics on available historical data.
2. the dataset always found in some dimension.If we have more than two features in the dataset then it is called multi-dimensional dataset.
3. It is possible to store multi dimensional data in list data structure but to access multi dimensional list we need to use numpy library.
4. modules provide us multiple methods which functionalities such as arraylist and many other functions are also available.
5. on historical data we can perform query row-wise and analysis can be done column-wise.
6. numpy provides some useful methods like sum, mean, max and many other.
7. data analytics means analyzing the given raw data and get some conclusion about the given data.
8. Data anlytics is the prediction of futuristic data by using the historical dataset.
9. data analysis means collecting, gathering, acquiring, cleaning, evalution and summarizing the given data.
10. understand the importance of data structure in computer science which play major role for job hiring.
and many more things...
Your work is highly appreciated.
Thank you for giving your precious time and making our country a nation of creators

[YashSharma-quuk]

Abstract:
>>>Data science
>>>List concept
>>>Dimensions
>>>Numpy liberary
>>>Data structure
>>>Query
>>>Data
Thank you sir🙏

[jahanvijain]

In this session i learned about data science, data structure, sets and actions, numpy, list, query on data, dimension, data analysis prediction and much more.

[ridhamanand]

1. Data structure means arranging the data in such a structure to suit a specific purpose so that we can do some operations on it like query, analysis, analytics.
2. Dataset means data arranged in row and columns
3. There are dimension of data, 1d means we have only one feature of one record. Data which has More than 1 dimensions is called multi-dimensional data.
4. Historical data means the data collected in past events.
5. introduction to numpy.
6. Data operations like query, data analysis and data analytics
7.query means finding different type of required data from the historical data.
8. data analysis means performing mathematical opertaions like mean, median, max, average etc on the historical data.
9. data analytics means using ai to predict the future data on the basis of historical data available, it required dl and ml to work on.
10. concepts of lists and arrays.
11. Typically all the data science operations are done on the data in columns.
12. Panda Library

[puneetmudgal]

Summary

Data Science
Data collection
Query
Data analysis
Data analytic
Data structures
Numpy and array

[shivamgupta]

Breif summary of things that I learnt from this session:-
1) Some basis about datastructure, datasets in python.
2) Some basis about numpy library, list, use of numpyarray() to convert list into array.
3) Unstructured data, data analysis and data analytics performed on different types of data.
4) Some basis about machine learning and Artificial intelligence.
5) Concept of queries and lists. How to store multidimensional array into list.

[yashlabhsetwar]

In the 13th session of the Python3 programming I learnt:
1) Three types of operation that is the query, data analysis, data analytics.
2) Introduction to the data science, AI, data sets.
3) Basic concept of list and query.
4) functions of numpy library.
5) Some things about ML.
6) max(), mean(), sum() functions.
7) conversion of list to numpy array.
8) python data structures and basic libraries.

[kmkaruna]

I learnt about this session :-
* Data Structure, data analysis and data set
* Numpy library and it's use caes
* How to convert a list in an array
* Some basic concepts of machine learning and AI
* query and dimension in data
*Other concept of paython...

[pankhurisharma]

In this session I learned:
- How we structure/format data varies from the requirement to requirement
- 1D- Knowing only 1 thing about the data, i.e. having only 1 column of information. Similarly 2D is 2 columns, 3D is 3 columns, etc.
- Smart data collection- Gather that much data such that each row can be identified uniquely
- Dataset- After the collection of data is done, the complete data is known as dataset
- Other names of row(horizontal) is record/object
- Other name of column(vertical) is information/feature
- We can do 3 operations on the dataset:
1. Query- search per record-wise
2. Data analysis- Calculating sum, mean, average, etc. per column-wise
3. Data analytics- Prediction
- Historical data- Data that is already available(both query & analysis is done on this data)
- Futuristic data- Data that isn't available, we predict this data such as in Analytics
- In list, we can store multi-dimensional data
- In the list, we can't do analysis as we can't do column-wise operations in the list
- Numpy library has a NumPy module whose functions can be seen by "dir(numpy)"
- In array() we can do both column & row-wise operations
- In NumPy array we can use many functions to perform on elements of the array, like sum(), max(), mean(), etc.
- In array, if we have strings then dtype becomes Unicode(U8) & we can't perform functions like max() etc. on it

[Rajkumar-obon]

Today i learnt about
1. Introduction on data science
2. Data structure
3. Numpy library, numpay.late()
4. Query
5. Concept of list
6. artificial intelligence
7. Machine learning
8. Array dimensions:1D, 2D

[SpeakSatvik]

20-12-2020
Today, we learnt about the numpy, list, operations on data, data structure.
We started with the discussion about what we are going to learn not ML, but the core concept so it will help in future to learn ML.
Proceed to the data structure, As we know today's world biggest company running b/c of the data, it's better to provide a nice structure for data in files so it will help us to easily retrieve it.
eg. if we want to store the student who purchase the course from lw then it's better to provide that much info about the student so we can uniquely identified the record.
Data stored in one feature to show us the info then it's called as 1dimension(1D means single info about the feature) if we have n features then it's called n dimensions.
Now it becomes the dataset which we can used for the data operation and their are three types of operation we can do 1) query 2)Data Analysis 3) Data analytics.
Query we done on the data for a particular record so we can say it's a row wise operation and some how we can use list and Data analysis we done for sum, mean, etc. and it's a column wise operation and we can perform query, Data analysis to the historical data.
Data analytics which we used for eg. if you want to know the new student which will come and want to purchase the course then which course will it choose? for that our mechanical device is not intelligent like our humans which is a most intelligent program in the history so to make our mechanical device like human brain then here comes the artificial intelligence to predict like human.
In Data analytics, data science comes. Now we started the numpy which is a library and our module name is numpy and we saw lot's of function using dir() and here comes the array in which we can perform both row wise and column wise operation and as pandas also built on the numpy and We saw the limitation or we can say it's not made for it who? it's list, in list we can only perform row wise operation not column wise like if we store any file inside the list then it stored in 1D like and we can also create nD means multi dimension structure but storing the data and doing operation on the data is both different. We can do operation like student[4][6] but in array we do operations like student[ :, 3] means all row and go to 3 column and print it. Be continue in next lecture.

[sonalipatil]

13th section
->Data science
->Data set
->Need of data
->Query and list
->Numpy library
->Arrays dimensions
Etc

[ArvindKumar-pynx]

Learnt in this session
About Data science, data sets, Data structures, data query, data analysis, data analytics, AI( Artificial intelligence),
learnt about Array dimension like 1D, 2D, 3D
numpy functions such as mean(), max(), sum()

[akshatjainit]

In today's session
- we learnt about query, data analysis
- we learnt about dataset how to import it and use it
- we learnt about numpy
- we learnt about how to operate data columnwise

[purusharma]

We learnt
Intro of data science
Dataset
Data structure
Bumpy

Analysis analytic query

[mdfaizanalam]

11 /10/2020

> Dimension is normally referred to as the number of features or columns present in a dataset. It can be represented as 1D, 2D, 3D....nD.
> We can perform query and data analysis on historical data.
> Yes, We can store the multidimensional data structure in a list.
> Functions in a module provide a set of code that can be used directly by importing the module.
> Data analysis is a part of Dataset where it performs some operation of given data, such as sum/count/average of data. It is only possible to analysis the data, if dataset/data is available.
> Data analytics is the science of analyzing raw data in order to make conclusions about that information.
> To perform operations effectively and to utilize computer resources we required datastructure.
> AI uses different techniques to predicts the future results, this will help in machines to find future results.

[yahvirajsoni]

In this session learned about:- data science, list concept, dimension, numpy libraries, data structures, about artificial intelligence, query, data analysis, about machine learning, etc.

[paarthgupta]

In session 13 i learned..
Data science
List concept
Dimensions
Numpy library
Query
Data analytics