This notebook contains my notes for Predictive Analysis on Binary Classification. It acts as a cookbook. Importing and sizing up a New Data Set The file is comma delimited, with the data for one experiment occupying one line of text. This makes it a simple matter to read a line, split it on the comma […]
This notebook will show you how to install the course libraries, create your first Spark cluster, and test basic notebook functionality. To move through the notebook just run each of the cells. You will not need to solve any problems to complete this lab. You can run a cell by pressing “shift-enter”, which will compute […]
In [20]: import pandas as pd import numpy as np In [ ]: # Take few samples for the visualization sample_fbcheckin_train_tbl = fbcheckin_train_tbl[:10000].copy() In [21]: df = pd.read_csv(‘train.csv’, index_col=’row_id’) In [22]: df.head() Out[22]: x y accuracy time place_id row_id 0 0.7941 9.0809 54 470702 8523065625 1 5.9567 4.7968 13 186555 1757726713 2 8.3078 7.0407 74 322648 1137537235 3 7.3665 2.5165 […]
This script is my attempt for time series analysis. Pandas has dedicated libraries for handling TS objects, particularly the datatime64[ns] class which stores time information and allows us to perform some operations really fast. In [40]: import pandas as pd import numpy as np #import matplotlib.pylab as plt #%matplotlib inline import seaborn as sns #from matplotlib.pylab […]
Hi! I signed up for the course in Coursera called The Data Scientist’s Toolbox by Johns Hopkins University. I liked the course for providing an easy and comprehensive list of tools required by a data scientist. It covers various topics as to what you need as a data scientist. It is simple and concise with […]