A collection of learning outcomes data analysis using Python and SQL, from DQLab.

Overview

Data Analyst with PYTHON


Data Analyst berperan dalam menghasilkan analisa data serta mempresentasikan insight untuk membantu proses pengambilan keputusan manajerial pada suatu perusahaan. Tipe pemodelan data yang dilakukan oleh Data Analyst beragam mulai dari Exploratory hingga Predictive Modeling menggunakan algoritma machine learning untuk menemukan pola pada data yang diolah.


Repositori ini, saya gunakan untuk menyimpan dan berbagi hasil pembelajaran mengenai dasar analisis data dengan menggunakan 2 bahasa pemrograman, yaitu: PYTHON dan SQL. Terdapat juga tugas project dari beberapa praktisi yang didasarkan case study di lapangan.



MATERI


PYTHON

PYTHON for Data Professional Beginner - Part 1

PYTHON for Data Professional Beginner - Part 2

PYTHON for Data Professional Beginner - Part 3

Exploratory Data Analysis with PYTHON for Beginner

Fundamental Data Visuzlization with PYTHON

Data Visualization with PYTHON Matplotlib for Beginner - Part 1

Data Visualization with PYTHON Matplotlib for Beginner - Part 2



SQL

Fundamental SQL using SELECT Statement

Fundamental SQL using FUNCTION and GROUP BY Statement

Fundamental SQL using INNER and UNION



PROJECT

Project Data Analysis for Retail Sales Performance Report

Project Data Analysis for B2B Retail Customer Analytics Report


Owner
Seeking of knowledges and learning for a lifetime
Detailed analysis on fraud claims in insurance companies, gives you information as to why huge loss take place in insurance companies

Insurance-Fraud-Claims Detailed analysis on fraud claims in insurance companies, gives you information as to why huge loss take place in insurance com

1 Jan 27, 2022
BasstatPL is a package for performing different tabulations and calculations for descriptive statistics.

BasstatPL is a package for performing different tabulations and calculations for descriptive statistics. It provides: Frequency table constr

Angel Chavez 1 Oct 31, 2021
This tool parses log data and allows to define analysis pipelines for anomaly detection.

logdata-anomaly-miner This tool parses log data and allows to define analysis pipelines for anomaly detection. It was designed to run the analysis wit

AECID 32 Nov 27, 2022
This cosmetics generator allows you to generate the new Fortnite cosmetics, Search pak and search cosmetics!

COSMETICS GENERATOR This cosmetics generator allows you to generate the new Fortnite cosmetics, Search pak and search cosmetics! Remember to put the l

ᴅᴊʟᴏʀ3xᴢᴏ 11 Dec 13, 2022
Hidden Markov Models in Python, with scikit-learn like API

hmmlearn hmmlearn is a set of algorithms for unsupervised learning and inference of Hidden Markov Models. For supervised learning learning of HMMs and

2.7k Jan 03, 2023
Flood modeling by 2D shallow water equation

hydraulicmodel Flood modeling by 2D shallow water equation. Refer to Hunter et al (2005), Bates et al. (2010). Diffusive wave approximation Local iner

6 Nov 30, 2022
Pipeline to convert a haploid assembly into diploid

HapDup (haplotype duplicator) is a pipeline to convert a haploid long read assembly into a dual diploid assembly. The reconstructed haplotypes

Mikhail Kolmogorov 50 Jan 05, 2023
Time ranges with python

timeranges Time ranges. Read the Docs Installation pip timeranges is available on pip: pip install timeranges GitHub You can also install the latest v

Micael Jarniac 2 Sep 01, 2022
This creates a ohlc timeseries from downloaded CSV files from NSE India website and makes a SQLite database for your research.

NSE-timeseries-form-CSV-file-creator-and-SQL-appender- This creates a ohlc timeseries from downloaded CSV files from National Stock Exchange India (NS

PILLAI, Amal 1 Oct 02, 2022
apricot implements submodular optimization for the purpose of selecting subsets of massive data sets to train machine learning models quickly.

Please consider citing the manuscript if you use apricot in your academic work! You can find more thorough documentation here. apricot implements subm

Jacob Schreiber 457 Dec 20, 2022
The repo for mlbtradetrees.com. Analyze any trade in baseball history!

The repo for mlbtradetrees.com. Analyze any trade in baseball history!

7 Nov 20, 2022
A python package which can be pip installed to perform statistics and visualize binomial and gaussian distributions of the dataset

GBiStat package A python package to assist programmers with data analysis. This package could be used to plot : Binomial Distribution of the dataset p

Rishikesh S 4 Oct 17, 2022
INFO-H515 - Big Data Scalable Analytics

INFO-H515 - Big Data Scalable Analytics Jacopo De Stefani, Giovanni Buroni, Théo Verhelst and Gianluca Bontempi - Machine Learning Group Exercise clas

Yann-Aël Le Borgne 58 Dec 11, 2022
PyEmits, a python package for easy manipulation in time-series data.

PyEmits, a python package for easy manipulation in time-series data. Time-series data is very common in real life. Engineering FSI industry (Financial

Thompson 5 Sep 23, 2022
PCAfold is an open-source Python library for generating, analyzing and improving low-dimensional manifolds obtained via Principal Component Analysis (PCA).

PCAfold is an open-source Python library for generating, analyzing and improving low-dimensional manifolds obtained via Principal Component Analysis (PCA).

Burn Research 4 Oct 13, 2022
Snakemake workflow for converting FASTQ files to self-contained CRAM files with maximum lossless compression.

Snakemake workflow: name A Snakemake workflow for description Usage The usage of this workflow is described in the Snakemake Workflow Catalog. If

Algorithms for reproducible bioinformatics (Koesterlab) 1 Dec 16, 2021
A Python Tools to imaging the shallow seismic structure

ShallowSeismicImaging Tools to imaging the shallow seismic structure, above 10 km, based on the ZH ratio measured from the ambient seismic noise, and

Xiao Xiao 9 Aug 09, 2022
Python library for creating data pipelines with chain functional programming

PyFunctional Features PyFunctional makes creating data pipelines easy by using chained functional operators. Here are a few examples of what it can do

Pedro Rodriguez 2.1k Jan 05, 2023
MEAD: A Large-scale Audio-visual Dataset for Emotional Talking-face Generation [ECCV2020]

MEAD: A Large-scale Audio-visual Dataset for Emotional Talking-face Generation [ECCV2020] by Kaisiyuan Wang, Qianyi Wu, Linsen Song, Zhuoqian Yang, Wa

112 Dec 28, 2022
Single machine, multiple cards training; mix-precision training; DALI data loader.

Template Script Category Description Category script comparison script train.py, loader.py for single-machine-multiple-cards training train_DP.py, tra

2 Jun 27, 2022