Plotly Histogram Pandas Series

Data visualization library for F#. Below, notice how you can quickly create a dygraph interactive plot. A histogram is a representation of the distribution of data. Course Transcript - [Instructor] Plotly is a data visualization library that you can use to construct web-friendly d3. How to check the assumptions, conduct, and interpret a paired samples t-test using Python. In pandas we are hesitant to add functionality specific to a certain database (that might open a can of worms, sqlalchemy gives us this database agnostic appraoch). The product is online, social, and collaborative, me. Olivem 2020. ipynb Building good graphics with matplotlib ain't easy! The best route is to create a somewhat unattractive visualization with matplotlib, then export it to PDF and open it up in Illustrator. Plotly The plotly Python package is an open-source library built on plotly. The slowest-moving of the series (out of necessity), this first installment lays out the task and data at the risk of boring you. data in Business Intelligence , IPython Notebook , Python The report generated by the IPython notebook described in this post (or this Python script ) can be downloaded here. You are just missing one last step. It sets the r and t properties to two lists of input values. Displayed below are the first 5 rows of the DataFrame we imported (to see the last n rows use. bins : int or sequence of scalars or str, optional If bins is an int, it defines the number of equal-width bins in the given range (10, by default). This tutorial is essentially for anyone who wants to create intuitive data visualizations using the Matplotlib library. I am plotting a series histogram in Pandas as follows: df['Primary Type']. ←Home Subscribe Grouped "histograms" for categorical data in Pandas November 13, 2015. Data Pre-Processing like normalization, train test split, Handling missing data. Questions: In ipython Notebook, first create a pandas Series object, then by calling the instance method. They are extracted from open source Python projects. value_counts(). Plotly Express is a great option for exploring pandas dataframes. table library frustrating at times, I’m finding my way around and finding most things work quite well. First, keep only the columns we need. plot in pandas. However assigning the width of a bar chart does not work as expected if a pandas series is passed - the trace is not displayed. GitHub Gist: instantly share code, notes, and snippets. Plotly is a collaborative, web-based graphing and analytics platform. bins : argument for matplotlib hist(), or None, optional Specification of hist bins, or None to use Freedman-Diaconis rule. If you need to fix a certain number of bins, you can use the argument bins and specify a number of bins, or give it directly the boundaries between each bin. One that has gotten a respectable amount of attention lately is pandas, a library that offers data structures and operations for manipulating numerical tables and time series. test ggplot2 bot master ; cookbook-axes-flevels: cookbook-axes-ylim. NumPy's np. py, which is not the most recent version. This example will show you how to leverage Plotly’s API for Python (and Pandas) to visualize data from a Socrata dataset. See our Version 4 Migration Guide for information about how to upgrade. OK, I Understand. A 2D density plot or 2D histogram is an extension of the well known histogram. Changes sometimes when we add new data to the dataset. April 6, 2018 — 0 Comments. As an example, we will create a plot of video game sales by country and year. Count Values In Pandas Dataframe. hist(), the browser displays the figure. Migrated to the latest version of Plotly and have troubles to display date time data in a Scatter plot. ちと、教えてもらったので、メモメモ。 データフレームDataFrame(正確にはシリーズSeries)で、特定文字を検索する方法。 grepだね。. Harvard Business Review has termed data science as the sexiest job of the 21st century. Calling the hist() method on a pandas dataframe will return histograms for all non-nuisance series in the dataframe: Since you are only interested in visualizing the distribution of the session_duration_seconds variable, you will pass in the column name to the column argument of the hist. By continuing to use Pastebin, you agree to our use of cookies as described in the Cookies Policy. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. " colref_list_type = " list of str or int, or Series or array-like " colref_list_desc = (" Either names of columns in `data_frame`, or pandas Series, or array_like objects ") docs = dict (data. Clone via HTTPS Clone with Git or checkout with SVN using the repository's web address. Pandas is a Python open source library for data science that allows us to easily work with structured data, such as csv files, SQL tables, or Excel spreadsheets. Importing a csv using a custom function to parse dates import pandas as pd def parse_month(month): """ Converts a string from the format M in datetime format. If you'd like to know more about this type of plot, visit this page for more information. Databricks supports Plotly 2. Plotly and Business intelligence tool Tableau. The more you learn about your data, the more likely you are to develop a better forecasting model. Full source and data. The left side of the graph represents the blacks or shadows, the right side represents the highlights or bright areas and the middle section is mid-tones (middle or 18% grey). Mon 08 April 2013. Additional keyword arguments are passed to the function used to draw the plot on the joint Axes, superseding items in the joint_kws dictionary. to_datetime(). At Plotly, most of our projects adhere to semver which means that in the 1. py, which is not the most recent version. First we’ll show an example of a standard time series graph. connect( db_file ) train. One technique essential to high-dimensional data visualization is the ability to arrange multiple views. Make bar charts, histograms, box plots, scatter plots, line graphs, dot plots, and more. With subplot you can arrange plots in a regular grid. Pandas Split String Into Columns. The interactive range slider allows users to select and drilldown into specific areas of the graph. - [Narrator] Let's look at how to build…statistical plots in Plotly. Advanced or Multi-Level Indexing. histogram-plot-using-python-pandas-dataframe. how to retrieve historical data across asset classes via the Eikon Data API, how to work with such data using pandas, Plotly and Cufflinks and; how to apply machine learning (ML) techniques for time series prediction. Pandas - How to read text files delimited with fixed widths With Python Pandas library it is possible to easily read fixed width text files, for example: In this case, the text file has its first 4 lines without data and the 5th line with the header. Tour de France Data Analysis using Strava data in Jupyter Notebook with Python, Pandas and Plotly - Step 1: single rider loading, exploration, wrangling, visualization Tour de France Data Analysis using Strava data in Jupyter Notebook with Python, Pandas and Plotly - Step 2: combining and aligning multi rider data for analyzing and visualizing the Race The Full Oracle OpenWorld and CodeOne. To create a histogram for a single column in a Pandas DataFrame, begin by importing all the required libraries. I am wondering how to save this figure to a file (I mean not by right click and save as, but the commands needed in the script. I have seen a few solutions that take a more iterative approach, creating a new layer in the stack for each category. x = x_values_subset. js, which in turn is. Calling the plotly API in the language/ tool of your choice. express functions ( px. Matplotlib’s histogram will default to using 10 bins, as the figure below shows. A histogram is a representation of the distribution of data. Donations help pay for cloud hosting costs, travel, and other project needs. Plotly is an analytics company known for developing real-time analytics, statistics and graphing tools for web-based application and standalone Python scripts. a plotly object Arguments (i. Suppose you have a dataset containing credit card transactions, including: the date of the transaction; the credit card number; the type of the expense. import plotly plotly. It is more effective than plotly. Histogram with plotly. plot in pandas. graph_objects charts objects (go. mean(),并将结果存储在stats字典中。. Level up your data visualisation. Sign in Sign up Instantly share code, notes. Call func on self producing a Series with transformed values and that has the same axis length as self. load_dataset('iris') # Make the plot parallel_coordinates(data, 'species', colormap=plt. figure_factory as plotly_tool. hist() method which gave me a plot as shown below: I want to represent the distribution for each value in a column with different. js JavaScript Graphing. How to make Histograms in Python with Plotly. Pandas and Plotly for Initial Data Analysis- A Tennis Example The Python Pandas library combined with the Pandas graphing library plotly, can aid in …. The key item to keep in mind is that styling presents the data so a human can read it but keeps the data in the same pandas data type so you can perform your normal pandas math, date or string functions. Plotting series using pandas Data visualization is often a very effective first step in gaining a rough understanding of a data set to be analyzed. To plot the histogram, In Step 1, we are asking Pandas to split the series into multiple values and the combine all of them into single column using the stack method. table library frustrating at times, I’m finding my way around and finding most things work quite well. Working with a time series of energy data, we’ll see how techniques such as time-based indexing, resampling, and rolling windows can help us explore variations in electricity demand and renewable energy supply over time. py建立在plotly. Make a histogram of the DataFrame’s. Importing the library adds a complementary plotting method plot_bokeh() on DataFrames and Series. Net : Search in Access Database - DataGridView BindingSource Filter Part 1/2. Some plotting examples from plot. Figure or plotly. DataFrame (iris. Pandas XlsxWriter Charts Documentation, Release 1. We need to specify the values that we are. Whether in finance, a scientific field, or data science, familiarity with pandas is essential. , in an externally created twinx), you can choose to suppress this behavior for alignment purposes. I will be using olive oil data set for this tutorial, you. In ipython Notebook, first create a pandas Series object, then by calling the instance method. Generate a bar chart with the values of maximum, minimum, average, 25 th percentile, 50 th percentile, and 75 th percentileby using ‘LifeExpectancy’ data with missing values (plotly and matplotlib). Histograms are an estimate of the probability distribution of a continuous quantitative variable. It is built on the Numpy package and its key data structure is called the DataFrame. Most of these are aggregations like sum(), mean. Pandas - data analysis. 16 The hist() function alone allows us to reference 3 famous algorithms by name (Sturges 1926; Freedman and Diaconis 1981; Scott 1979), but there are also. Learn how to create Plotly point maps. py, which is not the most recent version. It may be easiest to describe what it is by listing its more concrete components:. The figsize argument is used to specify the size of your figure and lw is the line width. hist (self, by=None, bins=10, **kwargs) [source] ¶ Draw one histogram of the DataFrame's columns. Importing Data in Python from different sources like. With plotly’s Python library, you can describe figures with DataFrame’s series and index, but with cufflinks you can plot it directly. Enter plotly, a declarative visualization tool with an easy-to-use Python library for interactive graphs. Questions: In ipython Notebook, first create a pandas Series object, then by calling the instance method. Dropping Rows Using Pandas The Art of Routing in Flask Extract Nested Data From Complex JSON Trees Make Your First API Calls with JQuery AJAX Manage Database Models with Flask-SQLAlchemy Making API Requests with node-fetch Configuring Python Projects with INI, TOML, YAML, and ENV files Turn JSON into Pandas DataFrames Scraping URLs with. Time series can be represented using either plotly. They are extracted from open source Python projects. This page is based on a Jupyter/IPython Notebook: download the original. This is accomplished by using the same axis object ax to append each band, and keeping track of the next bar location by cumulatively summing up the previous heights with a margin_bottom array. heatmaply: the most flexible option, allowing many different kind of customization. Olivem 2020. We have 1000 points, so 10 bins is a bit small, and makes our histogram look pretty blocky. Create a pandas Series object with indices given by the rst 10 letters of the English alphabet and values given by the rst 10 primes. Here we used Python, Pandas and Plotly to aggregate stock prices. Pandas - data analysis. figure_factory as plotly_tool. Plotly itself doesn't provide a direct interface for Pandas DataFrames, so plotting is slightly different to some of the other libraries. Try out a few examples of this, and display the results in Jupyter. This means you do not need a Plotly account or an internet connection to use this package. A histogram is a representation of the distribution of data. First we will load Pandas, Plotly and Cufflinks libraries. The output of Step 1. , attributes) passed along to the trace type. Bigrams Classification Corpus Cosine Similarity data. This binding guarantees that again, with just one single call, you can get a high quality data visualization of your dataframe content, with gems like automatic parsing and formatting of datetime values as well as inferred hues and labels management for your columns. They are extracted from open source Python projects. Before we turn to Seaborn and Plotly, discuss the simplest and often most convenient way to visualize data from a DataFrame: using its own plot() method. Pandas Tutorial: Data analysis with Python: Part 1. from pandas. We simply use the code weather. Time Series Analysis: A Simple Example with KNIME and Spark Seven Myths About the True Costs of AI Systems KDnuggets Home » News » 2018 » May » Opinions, Interviews » Overview of Dash Python Framework from Plotly for building dashboards ( 18:n22 ). May 4, 2018 — 0 Comments. Each column of your data frame will be plotted as an area on the chart. 详细layout布局设置请查询参考文档; Mark: Y轴禁用科学计数法:主要设置字段是:tickformat. pandaSDMX can expose datasets and related structural metadata including data flows, code-lists, and data structure definitions as pandas Series or MultiIndexed DataFrames. You need to specify the number of rows and columns and the number of the plot. plot(x_values_2, y_values_2) plt. For more examples of such charts, see the documentation of line and scatter plots. You will learn about making. This course teaches you to work with real-world datasets containing both string and numeric data, often structured around time series. Leave a Comment / By shanelynn. The scripts are available here. js之上,plotly. Dash is a Python framework for building analytical web apps in Python. Old Faithful with Multiple Axes, & Overlaid Histograms. Pandas time series tools apply equally well to either type of time series. Basic Plotting: plot. On the bottom right corner of the image, we also get an option to export the graph to Plotly's online gallery. histogram-plot-using-python-pandas-dataframe. 1; Filename, size File type Python version Upload date Hashes; Filename, size plotly-4. Lately I've been working a lot with dates in Pandas so I decided to make this little cheatsheet with the commands I use the most. Your code histogram to plotly is working. A histogram is a representation of the distribution of data. See our Version 4 Migration Guide for information about how to upgrade. colref_type = " str or int or Series or array-like " colref_desc = " Either a name of a column in `data_frame`, or a pandas Series or array_like object. Tiff histogram python. Data is delivered in DataFrame cufflinks. We also show the theoretical CDF. Bokeh is a fiscally sponsored project of NumFOCUS, a nonprofit dedicated to supporting the open-source scientific computing community. Published July 30, 2019 July 30, 2019 by modern. This line will trigger the update of the Histogram and the automatic rebinning. 3d Bar Plot In R. plotting import parallel_coordinates # Take the iris dataset import seaborn as sns data = sns. Matplotlib’s histogram will default to using 10 bins, as the figure below shows. hist() to draw a Matplotlib histogram of the input Series: import pandas as pd # Generate data on commute times. Let’s up the resolution by forcing matplotlib to use 20 bins instead. area() function. And give it a nickname of PD. We also saw how Plotly can be used to plot geographical plots using the choropleth map. Complete Python Pandas Data Science Tutorial! How do I apply a function to a pandas Series or DataFrame? - Duration: 17:58. Data or dict or list that describes a Plotly graph. Try out a few examples of this, and display the results in Jupyter. Observe that the histograms overlap. Navigation. Python plotting libraries are manifold. Make sure you've downloaded Plotly's Python library. Python Plotting Options. 0 The option of adding an alternative writer engineis only available in Pandas version 0. d3heatmap: a package that uses the same syntax as the base R heatmap() function to make interactive version. Lesson 1: Reading, slicing and plotting stock data. pandas DataFrames are the most widely used in-memory representation of complex data collections within Python. This article will focus on explaining the pandas pivot_table function and how to use it for your data analysis. A histogram is a representation of the distribution of data. Real world Pandas: Indexing and Plotting with the MultiIndex. You can vote up the examples you like or vote down the ones you don't like. bins : argument for matplotlib hist(), or None, optional Specification of hist bins, or None to use Freedman-Diaconis rule. Here we are plotting the histograms for each of the column in dataframe for the first 10 rows(df[:10]). Python Data Science Tutorials “Data science” is just about as broad of a term as they come. Pandas contains many built-in methods for grouping, filtering, and combining data, as well as the time-series functionality. Suppose you have a dataset containing credit card transactions, including: the date of the transaction; the credit card number; the type of the expense. hist (self, by=None, bins=10, **kwargs) [source] ¶ Draw one histogram of the DataFrame's columns. In this line, we update the underlying data of the histogram and set it to the new x_values_subset. If you need to fix a certain number of bins, you can use the argument bins and specify a number of bins, or give it directly the boundaries between each bin. In particular, I make a lot of bar charts (including histograms), line plots (including time series), scatter plots, and density plots from data in Pandas data frames. Learn how to use Plotly with Databricks. We use cookies for various purposes including analytics. datagen; Data extraction: Extract data from any Plotly chart. R is a programming language. 1 Graphical queries. Link to article: Big data analytics with Pandas and SQLite Please make comments or suggestions via email, issues, or pull requests. Pandas is a software library written for the Python programming language. Pandas Series is one-dimentional labeled array containing data of the same type (integers, strings, floating point numbers, Python objects, etc. In this post, we look at using Tablesaw's new open-source, plotting framework — Plot. Matplotlib Histograms This is a program that will produce histograms for height and weight import matplotlib. we import two plot functions from plotly. jl are: Make it convenient to construct and manipulate plotly visualizations. Let's look at some examples. The scripts are available here. Consider Plotly Enterprise – fully secure, on-premise instances of Plotly. William Playfair (1759 - 1823) was a Scottish economist and pioneer of this approach. Pandas is free software released under the three-clause BSD license. NumPy is a third-party Python library that provides support for large multidimensional arrays and matrices along with a collection of mathematical functions to operate on these elements. Generate HTML reports with Python, Pandas, and Plotly Published December 22, 2014 October 5, 2015 by modern. To evaluate the dataset, we use three different Python libraries: Pandas, Matplotlib, and Plotly. This binding guarantees that again, with just one single call, you can get a high quality data visualization of your dataframe content, with gems like automatic parsing and formatting of datetime values as well as inferred hues and labels management for your columns. One technique essential to high-dimensional data visualization is the ability to arrange multiple views. Python Pandas Series and DataFrame Plot Graph Introduction Matplotlib examples Please Subscribe my Channel : https://www. Pandas development started in 2008 with main developer Wes McKinney and the library has become a standard for data analysis and management using Python. We'll need to normalize this data so we can investigate across the different number of games in the regular season and the playoffs, and compare between the various teams that play a different number of games in the playoffs. The axis labels are collectively called index. In this case a dict containing the Lines making up the boxes, caps, fliers, medians, and whiskers is returned. GitHub Gist: instantly share code, notes, and snippets. Real world Pandas: Cut and Where. Post navigation. The numpy module is excellent for numerical computations, but to handle missing data or arrays with mixed types takes more work. By using plotly online, your data visualizations are automatically uploaded so that you can access them through the online interface, regardless of how you create them. Calling the plotly API in the language/ tool of your choice. This is useful when. The sklearn-pandas library looks great for bridging pandas scikit-learn. Enter plotly, a declarative visualization tool with an easy-to-use Python library for interactive graphs. On the bottom right corner of the image, we also get an option to export the graph to Plotly's online gallery. Plotly generates rich, interactive graphs using d3. In this line, we update the underlying data of the histogram and set it to the new x_values_subset. The histogram below shows that the target variable, Item_Outlet_Sales, is right skewed:. You can easily create and embed these graphs into HTML reports to share with your team using a well-known data science language, like Python, MATLAB, or R. This page is based on a Jupyter/IPython Notebook: download the original. Histogram chart made in Plotly. How to plot this time series plot in pandas where The x axis is the date and the y axis is the annual income and the plot is grouped by gender and state where there is one trace for female in state A another trace for female in state B and so on ?. Colors for branches other than Lines can be specified using a pandas Series with a MultiIndex. The xaxis shows units sold per day. Generate a bar chart with the values of maximum, minimum, average, 25 th percentile, 50 th percentile, and 75 th percentileby using ‘LifeExpectancy’ data with missing values (plotly and matplotlib). test ggplot2 bot master ; cookbook-axes-flevels: cookbook-axes-ylim. Plotly dark theme r. How to add legends and title to grouped histograms generated by Pandas Tag: pandas , matplotlib I am trying to plot a histogram of multiple attributes grouped by another attributes, all of them in a dataframe. concat takes a list of Series or DataFrames and returns a Series or DataFrame of the concatenated objects. gl之上,前者被广泛应用于印刷出版物和创建网站。 cufflinks是一个plotly的包装器(wrapper), 官方的原话是"a library for easy interactive Pandas charting with Plotly". In this article, we’ll get an introduction to the plotly library by walking through making basic time series visualizations. groupby (self[, by, axis, level, …]) Group DataFrame or Series using a mapper or by a Series of columns. Post navigation. data in Bioinformatics, Dash, R, rstats Create your own Salesforce Dashboard in Python with Dash Published September 30, 2018 September 30, 2018 by Amadou Kane in Business Intelligence , Dash , Dashboards , Data Visualization. In this exercise, you will work with a dataset consisting of restaurant bills that includes the amount customers tipped. Observe that the histograms overlap. For analysis and styling graphs, Plotly offers a Python sandbox (NumPy supported), datagrid, and GUI. 从上面的学习,我们看到了如何使用Python的基础工具搭建一个直方图,下面我们来看看如何使用更为强大的Python库包来完成直方图。. Plotly-----type Layout =. Plotly With Pandas. In this article, we'll get an introduction to the plotly library by walking through making basic time series visualizations. To create a histogram, we will use pandas hist() method. Plotly allows users to import, copy and paste, or stream data to be analyzed and visualized. I am wondering how to save this figure to a file (I mean not by right click and save as, but the commands needed in the script). Its creator, Wes McKinney, regularly posts materials and tutorials in his blog , and has written a very handy book on data analysis with python. js , you learned how to use Chart. plotly is an interactive visualization library. To plot wavelength and intensity on the x and y axes respectively with each different wafer number as it's own series, one can group data wrt wafer_number, and then deal with each group import pandas as pd from StringIO import StringIO import matplotlib. Hi Plotly Team, I may have stumbled across an inconsistency in the api for the bar chart trace. One day last week, I was googling "statistics with Python", the results were somewhat unfruitful. Histogram with Plotly Express¶. Importing histogram from matplotlib to plotly. Pandas defaults to storing data in DataFrames. Plotly connects to MySQL, Google Docs, Dropbox, SQLite, Tableau and more with Cron jobs or by pasting in a URL. matplotlib, pandas, plotly, seaborn [plotly] Interactive correlation matrix. Draw one histogram of the DataFrame’s columns. 0 The option of adding an alternative writer engineis only available in Pandas version 0. It is a great way to display a specific range within your chart, especially for time series plots. Plotly With Pandas. It provides tools for reading and writing data in different formats, carrying out. GeoSeries is a Series that holds (shapely) geometry objects (Points, LineStrings, Polygons, …). GitHub Gist: instantly share code, notes, and snippets. Python Data Science Distribution Python for Data Analysis Modern Data Analysis with pandas Time Series Analysis & Forecasting Shiny-like Apps for python Future of Data Access in Data Science Future of Data persistence in Data Science Self-Service Data in Enterprise Learn markdown Markdown Cheat Sheet How to build a site like this. import pandas as pd import numpy as np df = pd. …So we'll say. This means you do not need a Plotly account or an internet connection to use this package. ipynb Building good graphics with matplotlib ain’t easy! The best route is to create a somewhat unattractive visualization with matplotlib, then export it to PDF and open it up in Illustrator. This is called Interquartile (IQR) range = Q3 - Q1; Quartiles. bins : int or sequence of scalars or str, optional If bins is an int, it defines the number of equal-width bins in the given range (10, by default). With plotly, one can write R code to pose graphical queries that operate entirely client-side in a web browser (i. pyplot as plt data = \. py, which is not the most recent version. It sets the r and t properties to two lists of input values. ly – which provides its own Java visualization library and Java wrapper. …Also, I'll show you how to create a multiple histogram…chart plotted from a data frame,…and subplot histograms. Consider Plotly Enterprise – fully secure, on-premise instances of Plotly. we import two plot functions from plotly. API Reference. plotly is an interactive visualization library. We need to specify the values that we are. We have different types of plots in matplotlib library which can help us to make a suitable graph as you needed. The following are code examples for showing how to use plotly. histogram()或者np. 15 - a Jupyter Notebook package on PyPI - Libraries. The x axis is the time series (index of df1) and y axis is a numerical variable (B variable of df1). update_xaxes 设置等价于 plotly的layout设置,分别设置X轴,y轴. Pre-Requisites. histogram() uses matplotlib. Python Pandas Series and DataFrame Plot Graph Introduction Matplotlib examples Please Subscribe my Channel : https://www. histogram()或者np. Bigrams Classification Corpus Cosine Similarity data. WithOptions specifies how the chart looks, Chart. With plotly, one can write R code to pose graphical queries that operate entirely client-side in a web browser (i. A histogram is a representation of the distribution of data. What your plotly shows is a grouped bar chart. Staying in Python’s scientific stack, Pandas’ Series. The axis labels are often referred to as index. A DataFrame can be seen as a concatenation of Series, each Series having the same index, i. Pandas is a high-level data manipulation tool developed by Wes McKinney. …More specifically, I'm going to show you…how to build a simple histogram chart from a series object. For analysis and styling graphs, Plotly offers a Python sandbox (NumPy supported), datagrid, and GUI. It contains well written, well thought and well explained computer science and programming articles, quizzes and practice/competitive programming/company interview Questions. Plotly is an analytics company known for developing real-time analytics, statistics and graphing tools for web-based application and standalone Python scripts. You are just missing one last step. It shows the distribution of values in a data set across the range of two quantitative variables. The following example uses the Plotly online data analytics and visualization. It cames particularly handy when you need to organize your data models in a hierarchical fashion and you also need a fast way to retrieve the data.