Have you ever needed to create a DataFrame of "dummy" data, but without reading from a file? In this video, I'll demonstrate how to create a DataFrame from a dictionary, a list, and a NumPy array. I'll also show you how to create a new Series and attach it to the DataFrame.

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== RESOURCES ==
GitHub repository for the series: https://github.com/justmarkham/pandas-videos
"DataFrame" documentation: http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.html
"Series" documentation: http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.html
"set_index" documentation: http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.set_index.html
"concat" documentation: http://pandas.pydata.org/pandas-docs/stable/generated/pandas.concat.html
"np.arange" documentation: http://docs.scipy.org/doc/numpy/reference/generated/numpy.arange.html
"np.random" documentation: http://docs.scipy.org/doc/numpy/reference/routines.random.html

== RELATED VIDEOS ==
pandas index (part 1): https://www.youtube.com/watch?v=OYZNk7Z9s6I&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=17
pandas index (part 2): https://www.youtube.com/watch?v=15q-is8P_H4&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=18

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