This gist is created to store the atom configuration:
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from pyspark.sql.types import * | |
# Auxiliar functions | |
# Pandas Types -> Sparks Types | |
def equivalent_type(f): | |
if f == 'datetime64[ns]': return DateType() | |
elif f == 'int64': return LongType() | |
elif f == 'int32': return IntegerType() | |
elif f == 'float64': return FloatType() | |
else: return StringType() |
This project is part of the Udacity Data Analyst Nanodegree Project 5, with the aim of sharing knowledge with others. This is a dimplejs example based on the flight data from RITA that you can find at:
http://stat-computing.org/dataexpo/2009/the-data.html
The graph represents the evolution in terms of number of flights per year versus total distance accumulated per airline per year for the period between 1988 to 2008.
Check it out in b.locks: http://bl.ocks.org/kingkastle/raw/7188565a417968331fda/