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Solution

Solution: Python: Data Analysis
Solution: Python: Data Analysis

Join for an in-depth discussion in this video Solution, part of Python: Data Analysis.

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Skill Level Intermediate
2h 16m
Duration
510,592
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Q: The course shows how to download files from FTP and web servers using Python 3.X. How do I do the same thing with Python 2.7?

A: First import urllib, then use urllib.urlretrieve(URL,filename). For instance, to download the stations.txt files used in the chapter 5 video “Downloading and parsing data files,” you’d do urllib.urlretrieve(‘ftp://ftp.ncdc.noaa.gov/pub/data/ghcn/daily/ghcnd-stations.txt','stations.txt').

Q. What are the issues with DataFrame.sort()?
 

A: Since Pandas version 0.18, the DataFrame method sort() was removed in favor of sort_values(). Unlike sort(), the new method does not sort records in place unless it is given the option "inplace=True". The following lines of code in the video need changing: 

  • In Chapter 6: Introduction to Pandas/DataFrames in iPandas
    • twoyears = twoyears.sort('2015',ascending=False) -> twoyears = twoyears.sort_values('2015',ascending=False)
  • In Chapter 7: Baby names with Pandas/A yearly top ten
    • allyears_indexed.loc['M',:,2008].sort_values('number',ascending=False).head()
    • pop2008 = allyears_indexed.loc['M',:,2008].sort_values('number',ascending=False).head()
    • def topten(sex,year):
      • simple = allyears_indexed.loc[sex,:,year].sort_values('number',ascending=False).reset_index()
  • In Chapter 7: Baby names with Pandas/Name Fads
    • [in addition to lines above, which are used to initialize the "name fads" computation]
    • spiky_common = spiky_common.sort_values(ascending=False)
    • spiky_common = spiky_common.sort_values(ascending=False); spiky_common.head(10)
  • In Chapter 7: Baby names with Pandas/Solution
    • [in addition to lines above, which are used to initialize the "name fads" computation]
    • totals_both = totals_both.sort_values(ascending=False)

Skills covered in this course
Big Data Developer IT Programming Languages Pandas NumPy Python

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