05 Reading stem and leaf plots

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import plotly.graph_objects as go
import stemgraphic

import findspark; findspark.init()
from pyspark.context import SparkContext
from pyspark.sql.session import SparkSession
from pyspark.sql import functions as F
spark = SparkSession.builder.appName('statistics').master('local').getOrCreate()

WARNING: An illegal reflective access operation has occurred
WARNING: Illegal reflective access by org.apache.spark.unsafe.Platform (file:/home/runner/work/statistics/spark-3.1.3-bin-hadoop3.2/jars/spark-unsafe_2.12-3.1.3.jar) to constructor java.nio.DirectByteBuffer(long,int)
WARNING: Please consider reporting this to the maintainers of org.apache.spark.unsafe.Platform
WARNING: Use --illegal-access=warn to enable warnings of further illegal reflective access operations
WARNING: All illegal access operations will be denied in a future release

22/07/21 02:34:24 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).

dataset = [4, 11, 14, 16, 16, 17, 18, 23, 23, 26, 26, 31, 32, 34, 35, 37, 38]
stems = [0, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3]

plt.stem(stems, dataset)

<StemContainer object of 3 artists>

stemgraphic.stem_graphic(dataset)

(<Figure size 540x198 with 1 Axes>, <Axes:>)