Filter rows with same column values in Pandas dataframe

Filter rows with same column values in a Pandas dataframe.

Assume the following Pandas dataframe where Q1 & Q2 are charges. A charge can either be +1 or -1.

df = pd.DataFrame([[1,1],[-1,-1],[1,-1],[-1,1]], columns=['Q1', 'Q2'])

   Q1  Q2
0   1   1
1  -1  -1
2   1  -1
3  -1   1

The following code produces a dataframe where each row only contains opposite charges, i.e if Q1 is 1, Q2 is -1 & vice versa.

df = df[ (df.Q1 == 1) & (df.Q2 == -1) | (df.Q1 == -1) & (df.Q2 == 1) ]

   Q1  Q2
2   1  -1
3  -1   1

2020 10
2019 24

2020

Measurement & mixed states for quantum systems.

9 minute read

Notes on measurement for quantum systems.

Quantum States as a generalization of classical probabilities.

51 minute read

Notes on quantum states as a generalization of classical probabilities.

Finding the ray_results folder in colab

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The location of ray_results folder in colab when using RLlib &/or tune.

PBT for MARL

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My attempt to implement a water down version of PBT (Population based training) for MARL (Multi-agent reinforcement learning).

RLlib trainer common config

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Ray (0.8.2) RLlib trainer common config from:

Output dimension from convolution layer

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How to calculate dimension of output from a convolution layer?

Changing G drive directory in Colab

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Changing Google drive directory in Colab.

Linear regression (Bayesian)

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Notes on the probability for linear regression (Bayesian)

RNN backprop thru time(BPTT part 2) \(\frac{\delta h_{t}} {\delta h_{t-1}}\)

22 minute read

Notes on the math for RNN back propagation through time(BPTT), part 2. The 1st derivative of \(h_t\) with respect to \(h_{t-1}\).

RNN backprop thru time(BPTT)

34 minute read

Notes on the math for RNN back propagation through time(BPTT).

2019

Filter rows with same column values in Pandas dataframe

9 minute read

Filter rows with same column values in a Pandas dataframe.

Custom Sagemaker reinforcement learning container

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Building & testing custom Sagemaker RL container.

Reinforcement learning custom environment in Sagemaker with Ray (RLlib)

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Demo setup for simple (reinforcement learning) custom environment in Sagemaker. This example uses Proximal Policy Optimization with Ray (RLlib).

Django + Postgres + Travis CI + Heroku CD

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Basic workflow of testing a Django & Postgres web app with Travis (continuous integration) & deployment to Heroku (continuous deployment).

Django + Postgres + Docker + Travis CI + Heroku CD

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Basic workflow of testing a dockerized Django & Postgres web app with Travis (continuous integration) & deployment to Heroku (continuous deployment).

Dockerized Postgres connection with Django web app in Travis CI

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Introducing a delay to allow proper connection between dockerized Postgres & Django web app in Travis CI.

Random policy in RLlib

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Creating & seeding a random policy class in RLlib.

Custom MARL (multi-agent reinforcement learning) CDA (continuous double auction) environment

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A custom MARL (multi-agent reinforcement learning) environment where multiple agents trade against one another in a CDA (continuous double auction).

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This post demonstrate how setup & access Tensorflow graphs.

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This post demonstrates how to create customized functions to bundle commands in a .bash_profile file on Mac.

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This post documents my implementation of the Random Network Distillation (RND) with Proximal Policy Optimization (PPO) algorithm. (continuous version)

DPPO distributed tensorflow

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This post documents my implementation of the Distributed Proximal Policy Optimization (Distributed PPO or DPPO) algorithm. (Distributed continuous version)

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This post documents my implementation of the A3C (Asynchronous Advantage Actor Critic) algorithm (Distributed discrete version).

A3C multi-threaded continuous version with N step targets

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This post documents my implementation of the A3C (Asynchronous Advantage Actor Critic) algorithm. (multi-threaded continuous version)

A3C multi-threaded discrete version with N step targets

70 minute read

This post documents my implementation of the A3C (Asynchronous Advantage Actor Critic) algorithm (discrete). (multi-threaded discrete version)

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This post demonstrates how to accumulate gradients with Tensorflow.

Distributed Tensorflow

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This post demonstrates a simple usage example of distributed Tensorflow with Python multiprocessing package.

N-step targets

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This post documents my implementation of the N-step Q-values estimation algorithm.

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This post demonstrates how to use the Python’s multiprocessing package to achieve parallel data generation.

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This post provides a simple usage examples for common Numpy array manipulation.

Dueling DDQN with PER

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This post documents my implementation of the Dueling Double Deep Q Network with Priority Experience Replay (Duel DDQN with PER) algorithm.

Dueling DDQN

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This post documents my implementation of the Dueling Double Deep Q Network (Dueling DDQN) algorithm.

DDQN

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This post documents my implementation of the Double Deep Q Network (DDQN) algorithm.

DQN

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This post documents my implementation of the Deep Q Network (DQN) algorithm.