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# Tom Ron tomron

Created Nov 17, 2020
Last active May 31, 2021
Back to back bar chart with Plotly
View plotly_back_to_back_chart.py
 import numpy as np import matplotlib.pyplot as plt import plotly.graph_objects as go women_pop = np.array([5., 30., 45., 22.]) men_pop = np.array( [5., 25., 50., 20.]) y = list(range(len(women_pop))) fig = go.Figure(data=[ go.Bar(y=y, x=women_pop, orientation='h', name="women", base=0),
Last active Jul 3, 2021
A nicer seasonal decompose chart using plotly.
View seasonal_decompose_plotly.py
 from statsmodels.tsa.seasonal import seasonal_decompose import plotly.tools as tls def plotSeasonalDecompose( x, model='additive', filt=None, period=None, two_sided=True, extrapolate_trend=0,
Created Jan 17, 2020
Code for post about networkx features - https://tomron.net/2020/01/17/3-interesting-features-of-networkx/
View networkx_post.py
 import networkx as nx import pandas as pd import numpy as np import matplotlib.pyplot as plt # Multigraph example G = nx.MultiGraph() G.add_nodes_from([1, 2, 3])
Last active Apr 30, 2019
Sequential probability ratio test implementation (https://en.wikipedia.org/wiki/Sequential_probability_ratio_test) for exponential distribution. Usage - `t = sprt.SPRT(0.05, 0.8, 1, 2); t.test([1, 2, 3, 4, 5])`
View sprt.py
 import numpy as np """ Implements Sequential probability ratio test https://en.wikipedia.org/wiki/Sequential_probability_ratio_test """ class SPRT: def __init__(self, alpha, beta, mu0, mu1):
Created Apr 30, 2019
Sequential probability ratio test
View sprt.py
 import numpy as np """ Implements Sequential probability ratio test https://en.wikipedia.org/wiki/Sequential_probability_ratio_test """ class SPRT: def __init__(self, alpha, beta, mu0, mu1):
Created Aug 6, 2018
welchtest.py - based on the lazy programmer ttest implementation (https://github.com/lazyprogrammer/machine_learning_examples/blob/master/ab_testing/ttest.py). Numbers are not exactly the same but I suspect it have to do with rounding issues
View welchtest.py
 import pandas as pd import numpy as np from scipy import stats input_file='advertisement_clicks.csv' df = pd.read_csv(input_file) a = df[df['advertisement_id']== 'A']['action'].tolist()
Created Aug 6, 2018
welchtest
View welchtest.py
 import pandas as pd import numpy as np from scipy import stats input_file='advertisement_clicks.csv' df = pd.read_csv(input_file) a = df[df['advertisement_id']== 'A']['action'].tolist()
Created Jul 20, 2017
Merge Map Spark User Defined Aggregation function - merge two maps of type <String, Long> to one Map.
View MergeMapUDAF.java
 package com.tomron; import org.apache.spark.sql.Row; import org.apache.spark.sql.expressions.MutableAggregationBuffer; import org.apache.spark.sql.expressions.UserDefinedAggregateFunction; import org.apache.spark.sql.types.DataType; import org.apache.spark.sql.types.DataTypes; import org.apache.spark.sql.types.StructField; import org.apache.spark.sql.types.StructType;
Created Jul 20, 2017
Merge Map Spark User Defined Aggregation function - merge two maps of type <String, Long> to one Map.
View MergeMapUDAF.java
 package com.tomron; import org.apache.spark.sql.Row; import org.apache.spark.sql.expressions.MutableAggregationBuffer; import org.apache.spark.sql.expressions.UserDefinedAggregateFunction; import org.apache.spark.sql.types.DataType; import org.apache.spark.sql.types.DataTypes; import org.apache.spark.sql.types.StructField; import org.apache.spark.sql.types.StructType;