Pie chart for categorical data in python. Plot a pie chart of animals and label the slices.

Plot 2D data on 3D plot; Demo of 3D bar charts; Create 2D bar graphs in different planes; 3D box surface plot; Plot Mar 4, 2024 · For example, if we have sales data categorized by region, we might want to plot a pie chart to understand the sales distribution better. We then want to label the wedges via annotations. Qualitative and Quantitative Data - Image Source. Apr 11, 2023 · Seaborn Barplot. Exploring Categorical Data in Python. Nominal data is categorical data that may be divided into groups, but these groups lack any intrinsic hierarchy or order. We first create some dictionaries of common properties, which we can later pass as keyword argument. Divide the sections equally in the pie chart since the categories are equally distributed. In matplotlib, the pie () function is used to create a pie chart. To create a pie chart, you must have a categorical variable that divides your data into groups. Therefore, it should not be missed in any categorical data analysis. Scatter plot. Jun 25, 2024 · 12. Pie charts are a graphical representation of data that displays data in a circular graph. The pandas series plot() function returns a matplotlib axes Jan 6, 2022 · I want to create pie charts based on all unique data points based on Column A with pie chart size coming from Column B. The size of each slice is proportional to the relative size of each category out of the whole. Categorical data analysis is crucial in data science for understanding the characteristics and relationships between variables that fall into distinct A Pie Chart is a visualization of univariate data that depicts the data in a circular diagram. Visit the installation page to see how you can download the package and As you can see the pie chart draws one piece (called a wedge) for each value in the array (in this case [35, 25, 25, 15]). Here is an example. Nominal data. All you have to do is use kind='pie' flag and tell it which column you want (or use subplots=True to get all columns). scatterplot(). I want to show the percentage of total no of people paid the EMI and not yet paid. The data is in a pandas data frame, and here is a toy example of what I've tried to do: Jul 10, 2024 · Effective visualizations are crucial for understanding data. style . Seaborn, a Python data visualization library, offers an easy and intuitive way to create stunning pie charts. Example 1: Bar Charts. countplot(x ='sex', data = df) Output: Explanation/Analysis. There are three common ways to perform univariate analysis on one variable: 1. A pie chart is a typical graph for showing the proportions of categorical data. Nominal Data Jul 1, 2024 · 4. Related course: Data Visualization with Matplotlib and Python. You would generally use a barplot when you have at least one categorical variable and one numeric variable. DataFrame({'a': ['table', 'chair', 'chair', 'lamp', 'bed'], 'b': ['lamp', 'candle This process of converting categorical data into numeric representation is known as encoding. displot(tips, x="day", shrink=. slices_hours contains the hour values while activities contains label. An example of a data set will be: ['Female', 'Female', 'Female', 'Male', 'Male', 'Female'] Apr 26, 2023 · In statistics, there are numerous ways to visualize your data, however, some of the most common ones are bar, pie, and Pareto charts. This page offers numerous examples of charts built using the PyWaffle library, ranging from basic Dec 13, 2017 · Pie charts are good to show proportional data of different categories and figures are usually in percentages here. The syntax is given below: matplotlib. Customize the chart as desired by adding a title, legend, or exploding slices. fuel > SOME_THRESHOLD: return row['index'] return 'Other'. Then change the labels to include the data values instead of the percentages. Nov 24, 2020 · I have a dataframe of categorical values, and want to tabulate, then make a pie graph on each column. When working with categorical data, it is important to understand the different types of plots that can effectively represent the data. The slices in the pie typically represent percentages of the total. This function wraps matplotlib. In conclusion, Exploratory Data Analysis (EDA) is crucial for understanding datasets, identifying patterns, and informing subsequent analysis. pie() for the specified column. >>> df. Each slice in the chart represents a category or a portion of the whole, with the size of the slice proportional to the corresponding data value. Nov 28, 2018 · 1. See examples of pie charts with different data, labels, colors, and customizations. 6, shadow=False, Jan 23, 2023 · You can customize the type of visualization that is created by using the kind= parameter. 3. The python library ‘matplotlib’ provides many useful tools for creating beautiful visualizations, including pie charts. autopct = '%. In the outer circle, we'll plot them as members of their To plot a pie chart, pass 'pie' to the kind parameter. The axes Matplotlib object has a baked in pie method, as does the higher level pyplot library. To visualize your data, you can build a scatter plot from scratch. Types of Categorial Data. go charts. startangle… Dec 15, 2019 · My dataframe has two columns: "Name" and "EMI_Paid" and I want plot a pie chart for column "EMI paid". Sep 4, 2020 · Instead, I would create a pie chart or one of its variations. Well, as we see here, the donut is a pie, having a certain width set to the wedges, which is different from its radius. Here’s a simple example that demonstrates how to generate a my real data. #. Feb 8, 2023 · A bar chart is a chart or graph that represents numerical measures (such as counts, means, etc. pyplot. If you have lots of categories it can be cumbersome to manually set a colour for each category May 20, 2024 · Data visualization is an essential aspect of data analysis, aiding in the interpretation and communication of insights. This article describes mainly Plotly . Jan 25, 2021 · You only need to groupby the state first and then use count just like so: >>> import pandas as pd. Nov 27, 2015 · My y values are float, whereas x values are categorical data. Oct 3, 2017 · The file patient1. Plot a pie chart of animals and label the slices. This means, my legend will contain the color and type ( Female or Male) and in the pie chart, there will be the Prozent of each gender. City Population abc 5000 mno 2000 xyz 7000 uvw 9000 def 11000 I need pie chart for this with three categoies , underpopulated where population < 5000, moderate-populated where 5000 < population < 10000, and overpopulated where population > 10000. Two, sometimes the widths for the slices are not intuitively clear. I am able to do this in a count plot but unable to do it in a pie chart - COUNT PLOT: sns. 10. This function also displays a table of frequencies and proportions and performs a Chi-square test for checking the equality of probabilities. ] I want to plot them in pie charts of any suitable graphs, without using matplotlib. Jun 20, 2020 · python stacked bar chart using categorical data. DataFrame. To add labels, pass a list of labels to the labels parameter. Some common types of plots for categorical data include bar plots, pie charts, and stacked bar plots. Summary statistics – Measures the center and spread of values. PCA is mainly used for continuous variables. If no column reference is passed and subplots=True a pie plot is drawn for each numerical column independently. Each bar’s width in the bar chart is the same, meaning each bar’s area is also proportional to the counts they represent. import seaborn. go) library allows you to customize your charts with ease. The data can be placed into a pie plot, as others have shown, but that doesn't mean it should be. In other words, the parts/slice of the graph is proportionate to the fraction of the whole in each category. df. It's not working I found examples looks like this, but I couldn't managed my problem. Sep 8, 2022 · Photo by Elle inlom on Unsplash. Cars: [FORD, FORD, BMW, GMC, GMC, GMC, GMC. Jan 22, 2017 · My task is to create pie charts showing the % of emotions for each type of business. Only different levels are e. 3 11022 GE 500. Each row of pies represents seven core properties for a single cluster: from the contract term on the left to the TV streaming option on the right. https://pandas. The Seaborn catplot() function provides a figure-level interface for creating categorical plots. Python3. I could filter my values, but I have no idea how can I build and combine graphs. This article explores descriptive statistics and visualization techniques in R Programming Language for categorical data, focusing on frequencies, proportions, bar charts, pie charts, frequency tables, and contingency tables. 2f' # display the percentage value to 2 decimal places. In the inner circle, we'll treat each number as belonging to its own group. Scatteplot is a classic and fundamental plot used to study the relationship between two variables. plot(). This article solves this problem by illustrating how to plot a pie chart with DataFrame. The pie chart shown here represents the marital status of 500 adults in Santa Clara County taken from the 200 census, the same data that was represented by a bar graph in a previous Aug 24, 2022 · I want to plot the values from fruit to a pie chart to get a visual representation of the distribution of each individual fruit. Categorial Data is mainly divided into two main categories: Nominal Categorial Data; Ordinal Categorial Data; They can be represented in pie charts and bar graphs respectively. Seaborn does not implement pie charts. import numpy as np import pandas as pd import seaborn as sns from matplotlib import pyplot as plt plt . Agreeing with @DIMKOIM, Multiple Correspondence Analysis is your best bet. In this post, we will discuss how to use ‘matplotlib’ to create pie charts in python. C - pie chart3 contains information about different 'type'. For example, a dataset might have a column with the categories “red”, “green”, and “blue”. Let’s get started! May 18, 2023 · Pie charts are a popular way to represent data in a clear and concise manner. Jul 20, 2021 · The Python data visualization library Seaborn doesn’t have a default function to create pie charts, but you can use the following syntax in Matplotlib to create a pie chart and add a Seaborn color palette: Jul 4, 2022 · I have a data frame and I only want to plot the frequency of one column, for example, the count of cars of different brands. offline as py. pie () function to create the chart, providing the data and labels. This page shows examples of how to configure 2-dimensional Cartesian axes to visualize categorical (i. This is done via the wedgeprops argument. Series. Specify an output argument to store the PieChart object. Learn how to make pie charts in Python using Plotly Express and Plotly Graph Objects. PIE CHART : To visualize the numerical proportion occupied by each category, use the plt. Pie chart with categorical with PieChart If you want to display the group labels, in addition to the corresponding percentage for each group, you can use PieChart from lessR . and also I want change the label in Feb 28, 2022 · Syntax to install seaborn and matplotlib libraries: pip install seaborn. The problem is that I need to link the data of one column to the filtered data of the second column, without changing the dataset. We’ll use the matplotlib version. People love to hate on pie charts, but they have the same benefit as a mosaic/tree; they help keep proportion-to-the-whole interpretable. It's as easy as it gets. countplot(x="LoanStatus",data=df) EXPECTED: A pie chart showing how many values are there with both the loan status along with the percentage. plot(kind='pie') The most straightforward way to build a pie chart is to use the pie method. If you want to show the % symbol on the pie chart, you have to write/add: Jul 27, 2018 · A - pie chart1 contains information about different 'type'. Show Code. pyplot as plt. If one of the main variables is “categorical” (divided Jan 16, 2023 · In this guide, you’ll learn how to use the Seaborn countplot() function to create informative count plots. Jan 15, 2023 · Pareto Chart. plot(kind='pie', subplots=True, figsize=(6, 4)) My dataframe consists of two columns - Country and Value (% distribution) and has about 25 countries listed. Aug 23, 2019 · This data is not well represented by a pie plot, because each company size is a separate population, which will require 6 pie plots to be correctly represented. pie(sizes[1:], labels=labels[1:], colors=[colours[key] for key in labels[1:]]) This works to create the plot: Here we see that the labels are represented by the same colours across both plots, as desired. offset_copy; Zorder Demo; 3D plotting. Feb 8, 2023 · Waffle charts are a great way to visualise categorical data, are aesthetically pleasing and easy for readers to understand — which is one of the key goals of effective data visualisations. You can use plotly to draw grouped bar charts. Basically, this is a circular graphic divided into slices to display the proportional contribution of data compared to a total. e. Pie charts are not very popular with the visualization community. pyplot as plt labels = 'Frogs', 'Hogs', 'Dogs', 'Logs' sizes = [15, 30, 45, 10] fig, ax = plt. ) broken out by a categorical variable. Once done, the plt. In order to achieve that, you should know the data type and its measurement level. pie(autopct='%. pip install matplotlib. Sure, you can create beautiful charts without this knowledge, but intrinsically the whole visualization process is governed by Nov 21, 2020 · 5 Pie chart. Categorical data can be visualized using bar graphs and pie charts, and in this section, we will practice making such visualizations. Such axes are a natural fit for bar charts, waterfall charts, funnel charts, heatmaps, violin charts and box plots, but can also be used with scatter plots and Mar 5, 2024 · Categorical data is a type of data in statistics that stores data into groups or categories using names or labels. Then, pass the array of values to the ‘labels’ parameter to add labels. Jun 15, 2022 · For example i have this following data. sns. Method 1: Basic Pie Chart. m = number of columns required in grid''' #get all the column names in the Jun 24, 2015 · Pandas. A pie plot is a proportional representation of the numerical data in a column. In the relational plot tutorial we saw how to use different visual representations to show the relationship between multiple variables in a dataset. Ask Question Asked 6 years, 2 months ago. I am concerned with a single column ( fruit) from my df: I want to plot the values from fruit to a pie chart to get a visual representation of the distribution of each individual fruit. In the examples, we focused on cases where the main relationship was between two numerical variables. Conclusion. data = [44, 45, 40, 41, 39] Dec 30, 2022 · Categorical data is a type of data that can be divided into distinct categories or groups. py. LabelStyle = "namedata"; Oct 8, 2021 · A countplot basically counts the categories and returns a count of their occurrences. 2. While you can plot basic pie charts using Plotly Express, the more generic Plotly graph objects (. y: A sequence of datapoints to be represented as bars. We'll first generate some fake data, corresponding to three groups. For one, the graph appears cluttered when the groups exceed four. By default the plotting of the first wedge starts from the x-axis and moves counterclockwise: Note: The size of each wedge is determined by comparing the value with all the other values, by using this formula: Feb 19, 2024 · Pie charts are used to present categorical data in a format that highlights how each data point contributes to a whole, that is 100%. A bar chart is the most common data visualization for displaying the numerical values of categorical data to compare various categories between them. I would like to only plot the top 10 countries by values (by highest %) and within the plot, calculate the remaining countries % value and give it Packed-bubble chart; Patheffect Demo; Print Stdout; Rasterization for vector graphics; Set and get properties; SVG Filter Line; SVG filter pie; Table Demo; TickedStroke patheffect; transforms. plotly draw graphs and chart very interactive and attractive. . qualitative, nominal or ordinal data as opposed to continuous numerical data). See full list on datascienceparichay. This opens up much more possibilities. Aug 15, 2019 · The only way I can think of is to manually see which categories make the chart messy, then eventually choose a threshold when manually creating a new dataframe that bundles categories: if row. Mar 4, 2022 · The pie chart is a classic because it is easy to read and interpret. I can tabulate my table and create one massive plot, but I do not think this meets my needs, and would prefer a pie graph for each column instead: df = pd. How to do this in matplotlib? My values: Plotting data with categorical x and y axes in python. I have read: How can I read inputs The bars of a bar chart have a couple of key features: They have lengths that are proportional to the counts they represent. To create a pie chart with Seaborn, we first need to import the necessary libraries: import seaborn as snsimport matplotlib. data = [1 2 3]; names = [ "Blueberry", "Pumpkin", "Lemon" ]; p = piechart (data,names); p. Pie Charts. Handling categorical data can be challenging because it cannot be processed in the same way as numerical data. Seaborn is a Python data visualization library based on matplotlib. Import libraries: import pandas as pd. The pie chart comprises 100% of all autopct enables you to display the percentage value of each slice using Python string formatting. With ordinal data, a type of categorical data, the sample is often divided into groups, and the responses have a defined order. One way to visualize and analyze It’s also possible to visualize the distribution of a categorical variable using the logic of a histogram. Frequency table – Describes how often different values occur. In order to perform EDA, we will require the following python packages. Effectively it is a bar shaped pie chart. pie() method is readily available for creating your pie chart. D) Data visualization is the way we input data into tables. In matplotlib, you can conveniently do this using plt. Dec 26, 2021 · The area of the slices is equal to the percentage of the parts of the data. Crafting a Pie Chart with Matplotlib. Seaborn provides a simple and intuitive function to create informative count plots that are simple to produce and easy to… Read More »Seaborn Countplot – Counting Categorical Data in Python Pie charts make sense to show a parts-to-whole relationship for categorical data, including ordinal and nominal data. offline import init_notebook_mode, iplot. init_notebook_mode(connected=True) from plotly. import matplotlib. pydata. plot(kind='pie') Here, s is the pandas series with categorical values which is converted to a series of counts using the value_counts() function. The categories are represented by rectangular bars of the same width and with heights (for vertical bar charts) or lengths (for horizontal bar charts) proportional to the numerical values that Sep 13, 2022 · There are three common ways to visualize categorical data: Bar Charts; Boxplots by Group; Mosaic Plots; The following examples show how to create each of these plots for a pandas DataFrame in Python. Categorical Data Categorical data i Nov 29, 2023 · A pie chart is a popular data visualization technique that visually represents data using slices or wedges of a circle. id state value. The pie charts further below help to understand the composition of every cluster. html. It is one of the most simple plots provided by the seaborn library. Data. If you have multiple groups in your data you may want to visualise each group in a different color. Bar charts are one of the most common and simple ways to represent categorical data. These graphs consist of a circle (i. These features make a bar chart super dependable for representing categorical data. There are two types of categorical data: nominal and ordinal. 1 24592 CA 200. Each category is represented with a slice in the 'pie' (circle). Vertical bar chart’s discrete data is categorical and therefore answers the question of “how many?” in each category. I could not find similar solutions. 577 6 7. It provides a high-level interface for drawing attractive and informative statistical graphics. value_counts(). com Jul 7, 2023 · a bar chart to show the distribution of class's level of Titanic passengers. May 26, 2020 · A pie chart is a type of data visualization that is used to illustrate numerical proportions in data. Click the card to flip 👆. 0 19292 CA 100. org/docs/reference/api/pandas. B - pie chart2 contains information about different 'type'. As you can see in the previous example, bar plots are easier to read than pie charts. First, import the necessary libraries, then define your data for the pie chart. To begin with, ensure you’ve imported the required module using: import matplotlib. , the pie) with slices representing subgroups. D - pie chart4 contains information about different 'type'. This means that the function allows you to map to a figure, rather than an axes object. Showing proportions with Pie charts. Defined a function to plot the pie charts, for all categorical variables in a dataframe. In a pie chart, the central angle, area, and arc A Waffle Chart represents categorical data using a grid of equally sized squares or rectangles, each colored or shaded to depict different categories or segments. It expresses the numerical ratio of parts of the whole in a variable as slices of a pie. Pie charts can be useful when utilized in the right context with the right data. For instance, using the pie chart, we can summarize the composition of customer gender in customer bank data. Nov 22, 2021 · You can remember this because the prefix “uni” means “one. It does this by using rectangular bars with heights (or lengths) that are proportional to different values. Relative frequency is the percentage of the total. Mar 21, 2022 · Pandas has this built in to the pd. So I need to create a function in matplotlib that reads the "Business" column and then builds a pie chart using each of the emotion categories for each row in the dataframe. read_csv Nov 15, 2021 · For categorical variables: the mode; for numerical values (MonthlyCharges and tenure): the median. Dec 18, 2023 · Categorical data, representing non-measurable attributes, requires specialized analysis. pie() function. Unlike seaborn plots, pie charts do not calculate 1. For example, autopct = '%. Aug 24, 2022 · 2. plot(kind='pie', y='fruit') But this gives a TypeError: '<' not supported between instances of 'str' and 'int'. 1. This will automatically add the labels for you and even do the percentage labels as well. They also provide a nicer looking alternative to pie charts. pie. Nov 3, 2023 · 3. Modified 6 years, Python Matplotlib Plotting Stacked Bar Chart. C) Data visualization helps users understand a UML diagram. The chart is shaped in a circular form like a pie and each Oct 1, 2017 · 0. For example, the pie chart below shows a simple monthly budget of this baker I know, where the total percentage is 100 and the total of the arc measures should be 360°. Pie charts and donut charts are popular choices for visualizing categorical The following plots represent the same variables displayed with pie charts and with bar plots. import plotly. pie(sizes, labels=labels) Each slice of the pie chart is a patches. I've already built a bar plot, but I am having no luck with the pie chart. Mar 30, 2022 · Pie chart by author. pie(x, explode=None, labels=None, colors=None, autopct=None, pctdistance=0. Each pie chart slice corresponds to a relative proportion of the category versus the entire group. Mar 4, 2022 · A pie chart is a circular statistical graphical chart, divided into slices that illustrate numerical proportions in data. Syntax: countplot([x, y, hue, data, order, …]) Example: Python3. Mar 13, 2019 · python; pandas; data-visualization; or ask your own question. Sep 6, 2022 · I am looking to plot this in a pie chart showing 60% of loan status is fully paid while 40% is defaulted. Vertical bar charts (column chart) are distinguished from histograms, as they do not display continuous developments over an interval. Nonetheless, pie charts can be useful in many situations, for instance, where the data is very unbalanced. Use the plt. Use pie charts to compare the sizes of categories to the entire dataset. subplots() ax. We can do a little better than that without straying from the built-in functionality. Again, we’ll load the necessary libraries and data. The main purpose of a pie chart is to showcase the distribution or composition A) Data visualization was created to help accessibility issues. Jun 12, 2022 · Implementation of Pie Charts in Python. If the goal is to compare data values locally, pie charts can be applied to facilitate reading since they are able to show each location's proportion compared with the others. The column "EMI_Paid" can have two values: 0 and 1. Mar 1, 2022 · This worked for me. In this case, pie takes values corresponding to counts in a group. To create pie charts, we need the Seaborn barplot() function to display data in a bar chart format, which will then be transformed into a pie chart. Aug 14, 2020 · Step 1: Import your data set and have a good look at the data. Pie charts are used to visualize the part-to-whole relationship. It shows the frequency or relative frequency of values in the data. Label or position of the column to plot. Apr 9, 2022 · Another way to represent categorical data is a pie chart, in which each slice of the pie represents the relative frequency or percentage of data in each category. So we'll go over how to code them up in Matplotlib, which happens to be pretty straighforward. We'll use the former in our examples but any of these could be coded up as colors=[colours[key] for key in labels]) ax[1]. #Function to plot Pie-Charts for all categorical variables in the dataframe def pie_charts_for_CategoricalVar(df_pie,m): '''Takes in a dataframe(df_pie) and plots pie charts for all categorical columns. Feb 8, 2021 · In the file name I have a column with Female or Male and I would like to create a pie visualization Female or Male. plot. You must be aware of read_csv () tool from pandas for reading csv files. Frequency is the amount of times that value appeared in the data. use ( 'fast' ) military = pd . It can be used for nominal type or categorical type variables. In fact I have to make this dynamic. It is named after Vilfredo Pareto, an Italian economist who developed the concept of the 80/20 rule – that 80% of wealth was owned by 20% of the population. Packages to import: Once we have imported the packages successfully, we will move on to importing our dataset. To make each location's data stand out, the trick is to separate each location's piece from the rest. Example 1: Let’s take an example of 5 classes with some students in it and plot a pie chart on the basic number of students in each class. import numpy as np. Use various plots like bar charts, pie charts, and heatmaps to represent categorical data. g. Some useful parameters of barplot() are: x: Categorical data to be represented on the x-axis. Vertical Bar Chart. answered Aug 19, 2018 at 20:19. 1f' # display the percentage value to 1 decimal place. Pie charts are used to show the composition of categorical data. Parameters: yint or label, optional. Regardless of the type of plot, the data must be in the correct shape for the plot API. Further, the ratio between male and female customers is 3:1. >>> import matplotlib. Discrete bins are automatically set for categorical variables, but it may also be helpful to “shrink” the bars slightly to emphasize the categorical nature of the axis: sns. Beltino Goncalves. The following code shows how to create a bar chart to visualize the frequency of teams in a certain pandas DataFrame: Create a pie chart from a numeric vector and a vector of names. Pie graphs are used to show the distribution of qualitative (categorical) data. To code a pie chart in Python, you can use libraries like Matplotlib or Seaborn. Python enables the creation of waffle charts through the PyWaffle library. 2 12492 GE 340. The following is the syntax: # pie chart using pandas series plot () s. csv contains data as: Name Surname Age fdgf bcbb 21 Yash Singhvi 19 Yash Singhvi 19 piyush daga 20 cvcv dfg 16 sdsd sdsd 65 dsfef fedf 12 rfef fefe 70 fdgf rgd 10 Actually, I want to plot pie chart of the patient of age 0-17,18-59,60+. I run: df. . A count plot is similar to a bar plot and a histogram and provides counts of categorical values. 1f') Visualizing categorical data. For example, for this data base, I want a pie chart for Paris and one for London. Jan 23, 2023 · You can customize the type of visualization that is created by using the kind= parameter. Here 1 means - Customer Paid the EMI and 0 means EMI not yet received. 8) Feb 2, 2018 · I have created a matplotlib pie chart: df. Waffle charts are square or rectangular displays made up of smaller squares in a grid pattern. Featured on Meta We spent a sprint addressing your requests — here’s how it went python stacked Data Science Foundations II | Data Visualization Fundamentals with Python | Visualizing Categorical Data Topics pie-chart data-visualization seaborn matplotlib bar-chart pitfall-pie-chart Feb 24, 2016 · I have a bunch of categorical data from a survey and I would like to plot it in the same way as shown here. Charts – Used to visualize the distribution of values. A Pareto chart is a type of graph used for visualizing categorical data sets, in which the categories are grouped and sorted by frequency or magnitude. Wedge object; therefore in addition to Jun 23, 2024 · Unlike numerical data, categorical data cannot be measured or ordered in a meaningful way. B) Data visualization is one way we share the story. ”. For a brief introduction to the ideas behind the library, you can read the introductory notes or the paper. bh cz qi ce cy uz ax qo lr ty