Lesson 20

Saving and Exporting Data

This lesson covers:

  • Saving and reloading data

This first block loads the data that was used in the previous lesson.

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# Setup: Load the data to use later
import pandas as pd

gs10_csv = pd.read_csv("data/GS10.csv", index_col="DATE", parse_dates=True)
gs10_excel = pd.read_excel("data/GS10.xls", skiprows=10,
                           index_col="observation_date")

Problem: Export to Excel

Export gs10_csv to the Excel file gs10-exported.xlsx.

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Problem: Export to CSV

Export gs10_excel to CSV.

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Problem: Export to HDF

Export both to a single HDF file (the closest thing to a "native" format in pandas).

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Problem: Import from HDF

Import the data saved as HDF and verify it is the same as the original data.

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Exercises

Exercise: Import, export and verify

  • Import the data in "data/fred-md.csv"
  • Parse the dates and set the index column to "sasdate"
  • Remove first row labeled "Transform:" (Hint: Transpose, del and transpose back, or use drop)
  • Re-parse the dates on the index
  • Remove columns that have more than 10% missing values
  • Save to "data/fred-md.h5" as HDF.
  • Load the data into the variable reloaded and verify it is identical.
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Exercise: Looping Export

Export the columns RPI, INDPRO, and HWI from the FRED-MD data to "data/variablename.csv" so that, e.g., RPI is exported to data/RPI.csv:

Note You need to complete the previous exercise first (or at least the first 4 steps).

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