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# Notebook from stefanpeidli/cellphonedb Path: scanpy_cellphonedb.ipynb <code> from IPython.core.display import display, HTML display(HTML("<style>.container { width:90% !important; }</style>")) %matplotlib inline import numpy as np import pandas as pd import matplotlib.pyplot as pl import scanpy as sc import cellph...
{ "repository": "stefanpeidli/cellphonedb", "path": "scanpy_cellphonedb.ipynb", "matched_keywords": [ "Scanpy" ], "stars": null, "size": 63150, "hexsha": "d000f1ce0f008b8f64f705810da78b9e62f26064", "max_line_length": 212, "avg_line_length": 45.3989935298, "alphanum_fraction": 0.3578463975 }
# Notebook from innawendell/European_Comedy Path: Analyses/The Evolution of The Russian Comedy_Verse_Features.ipynb ## The Analysis of The Evolution of The Russian Comedy. Part 3._____no_output_____In this analysis,we will explore evolution of the French five-act comedy in verse based on the following features: - The...
{ "repository": "innawendell/European_Comedy", "path": "Analyses/The Evolution of The Russian Comedy_Verse_Features.ipynb", "matched_keywords": [ "evolution" ], "stars": null, "size": 948447, "hexsha": "d002bc0e0081d73349f836a6e32db713d13f5fa2", "max_line_length": 157244, "avg_line_length": 383.05...
# Notebook from quantopian/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers Path: Chapter4_TheGreatestTheoremNeverTold/Ch4_LawOfLargeNumbers_PyMC3.ipynb # Chapter 4 `Original content created by Cam Davidson-Pilon` `Ported to Python 3 and PyMC3 by Max Margenot (@clean_utensils) and Thomas Wiecki (@twiecki) a...
{ "repository": "quantopian/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers", "path": "Chapter4_TheGreatestTheoremNeverTold/Ch4_LawOfLargeNumbers_PyMC3.ipynb", "matched_keywords": [ "STAR" ], "stars": 74, "size": 633929, "hexsha": "d002f51b520dfb6f7f7c8f13e0401f22dc925760", "max_line_leng...
# Notebook from ethiry99/HW16_Amazon_Vine_Analysis Path: Vine_Review_Analysis.ipynb <code> # Dependencies and Setup import pandas as pd_____no_output_____vine_review_df=pd.read_csv("Resources/vine_table.csv") _____no_output_____vine_review_df.head() _____no_output_____vine_review_df=vine_review_df.loc[(vine_review_df[...
{ "repository": "ethiry99/HW16_Amazon_Vine_Analysis", "path": "Vine_Review_Analysis.ipynb", "matched_keywords": [ "STAR" ], "stars": null, "size": 11488, "hexsha": "d00352c042e11023e04cd767f979253bf98e6a8d", "max_line_length": 156, "avg_line_length": 25.9322799097, "alphanum_fraction": 0.4093837...
# Notebook from bbglab/adventofcode Path: 2016/loris/day_1.ipynb # Advent of Code 2016_____no_output_____ <code> data = open('data/day_1-1.txt', 'r').readline().strip().split(', ')_____no_output_____class TaxiCab: def __init__(self, data): self.data = data self.double_visit = [] self....
{ "repository": "bbglab/adventofcode", "path": "2016/loris/day_1.ipynb", "matched_keywords": [ "STAR" ], "stars": null, "size": 10515, "hexsha": "d0042eab5854b447de51a429a272d3a09f8991fe", "max_line_length": 277, "avg_line_length": 36.5104166667, "alphanum_fraction": 0.4633380884 }
# Notebook from rabest265/GunViolence Path: Code/demographics_Lat_Long.ipynb <code> #API calls to Google Maps for Lat & Long_____no_output_____# Dependencies import requests import json from config import gkey import os import csv import pandas as pd import numpy as np _____no_output_____# Load CSV file csv_path = os....
{ "repository": "rabest265/GunViolence", "path": "Code/demographics_Lat_Long.ipynb", "matched_keywords": [ "STAR", "Salmon" ], "stars": null, "size": 51222, "hexsha": "d0069e2a36204df8606dc23f8e75ef7c3b8b2179", "max_line_length": 116, "avg_line_length": 26.0406710727, "alphanum_fraction": 0....
# Notebook from debugevent90901/courseArchive Path: ECE365/genomics/Genomics_Lab4/ECE365-Genomics-Lab4-Spring21.ipynb # Lab 4: EM Algorithm and Single-Cell RNA-seq Data_____no_output_____### Name: Your Name Here (Your netid here)_____no_output_____### Due April 2, 2021 11:59 PM_____no_output_____#### Preamble (Don't c...
{ "repository": "debugevent90901/courseArchive", "path": "ECE365/genomics/Genomics_Lab4/ECE365-Genomics-Lab4-Spring21.ipynb", "matched_keywords": [ "RNA-seq", "single-cell" ], "stars": null, "size": 1023042, "hexsha": "d00741055dc800ea60b86da8dd05cb6e0b604bae", "max_line_length": 602447, "avg_...
# Notebook from justinshaffer/Extraction_kit_benchmarking Path: code/Taxon profile analysis.ipynb # Set-up notebook environment ## NOTE: Use a QIIME2 kernel_____no_output_____ <code> import numpy as np import pandas as pd import seaborn as sns import scipy from scipy import stats import matplotlib.pyplot as plt impor...
{ "repository": "justinshaffer/Extraction_kit_benchmarking", "path": "code/Taxon profile analysis.ipynb", "matched_keywords": [ "microbiome", "QIIME2" ], "stars": null, "size": 23131, "hexsha": "d0096cb02dc68507e2b0cfb172642550ef65c2c8", "max_line_length": 246, "avg_line_length": 34.7834586466...
# Notebook from rpatil524/Community-Notebooks Path: MachineLearning/How_to_build_an_RNAseq_logistic_regression_classifier_with_BigQuery_ML.ipynb <a href="https://colab.research.google.com/github/isb-cgc/Community-Notebooks/blob/master/MachineLearning/How_to_build_an_RNAseq_logistic_regression_classifier_with_BigQuery_...
{ "repository": "rpatil524/Community-Notebooks", "path": "MachineLearning/How_to_build_an_RNAseq_logistic_regression_classifier_with_BigQuery_ML.ipynb", "matched_keywords": [ "RNA-seq" ], "stars": 16, "size": 53907, "hexsha": "d00c6cf71bdffc5e1414b4ece1a89cb27eb58159", "max_line_length": 1068, "av...
# Notebook from jouterleys/BiomchBERT Path: classify_papers.ipynb Uses Fine-Tuned BERT network to classify biomechanics papers from PubMed_____no_output_____ <code> # Check date !rm /etc/localtime !ln -s /usr/share/zoneinfo/America/Los_Angeles /etc/localtime !date # might need to restart runtime if timezone didn't ch...
{ "repository": "jouterleys/BiomchBERT", "path": "classify_papers.ipynb", "matched_keywords": [ "BioPython", "evolution", "neuroscience" ], "stars": null, "size": 31222, "hexsha": "d00d1fd31d99a85620063e299bc079d92cc907c1", "max_line_length": 31222, "avg_line_length": 31222, "alphanum_fr...
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