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Make Matplotlib look like R Setting x-axis major and minor labels Plotting multiple charts in an ipython notebook Creating a multi-line plot Plotting a heatmap Annotate a time-series plot Annotate a time-series plot #2 Generate Embedded plots in excel files using Pandas, Vincent and xlsxwriter Boxplot for each quartile of a stratifying variable docs read_csv in action appending to a csv Reading a csv chunk-by-chunk Reading only certain rows of a csv chunk-by-chunk Reading the first few lines of a frame Reading a file that is compressed but not by file, but is a general application of opening the file within a context manager and using that handle to read.

See here Inferring dtypes from a file Dealing with bad lines Dealing with bad lines II Reading CSV with Unix timestamps and converting to local timezone Write a multi-row index CSV without writing duplicates The best way to combine multiple files into a single Data Frame is to read the individual frames one by one, put all of the individual frames into a list, and then combine the frames in the list using docs Simple Queries with a Timestamp Index Managing heterogeneous data using a linked multiple table hierarchy Merging on-disk tables with millions of rows Avoiding inconsistencies when writing to a store from multiple processes/threads De-duplicating a large store by chunks, essentially a recursive reduction operation.

Because of the breadth of the sample, it provides more information than is available in other house price indexes.

It also provides housing economists with an improved analytical tool that is useful for estimating changes in the rates of mortgage defaults, prepayments and housing affordability in specific geographic areas. See HPI release dates The standard deviation of house price growth (accounting for the time between repeat sales).

The most important preconditions for using indexes for index).

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