Join Michele Vallisneri for an in-depth discussion in this video Name popularity, part of Introduction to Data Analysis with Python.
- We are ready to start analyzing the data.…The first thing we want to do is to track the popularity…of a name across all years.…While we do that, we will see how to set and sort indexes,…how to select a row by the value of a MultiIndex,…and how to make a stacked plot in matplotlib.…So let's go to the IPython Notebook…and select the 07_03_popularity_begin exercise file.…This notebook contains all the code…that we developed in the last video.…
We're going to continue from that.…So let's execute all the cells…by selecting the Cell Menu and Run All.…We need to rework this data…in a way that will let us look at the changing popularity…of a given name.…We will do this using Panda's MulitIndexes.…We will index the data on gender first,…then name, then year.…So we build a new DataFrame...…where we set the index using sex first,…then name, then year.…We will also sort the index.…
Let's have a look.…Let me call this "allyears_indexed".…This looks good.…As we said before, indexing can be confusing in Pandas.…We use the special indexing attributes loc and iloc…
- Writing and running Python in iPython
- Using Python lists and dictionaries
- Creating NumPy arrays
- Indexing and slicing in NumPy
- Downloading and parsing data files into NumPy and Pandas
- Using multilevel series in Pandas
- Aggregating data in Pandas
Skill Level Intermediate
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 <span style="font-family: Courier;">import urllib</span>, then use <span style="font-family: Courier;">urllib.urlretrieve(URL,filename)</span>. For instance, to download the stations.txt files used in the chapter 5 video “Downloading and parsing data files,” you’d do <span style="font-family: Courier;">urllib.urlretrieve(‘ftp://ftp.ncdc.noaa.gov/pub/data/ghcn/daily/ghcnd-stations.txt','stations.txt')</span>.
1. Installation and Setup
2. Refresher: Data Containers in Python
3. Word Anagrams in Python
4. Introduction to NumPy
5. Weather Data with NumPy
6. Introduction to Pandas
7. Baby Names with Pandas
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