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130130* [ How to convert JSON to Excel with Python and pandas] ( https://www.marsja.se/how-to-convert-json-to-excel-python-pandas/ )
131131 provides instructions for creating a spreadsheet out of JSON file.
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133+ * [ Loading large datasets in Pandas] ( https://towardsdatascience.com/loading-large-datasets-in-pandas-11bdddd36f7b )
134+ explains how to get around the ` MemoryError ` issue that occurs
135+ when using ` read_csv ` because the data set is larger than the
136+ available memory on a machine. You can use chunking with
137+ the ` read_csv ` function to divide the data set into smaller parts that
138+ each can be loaded into memory. Alternatively, you can use a
139+ [ SQLite database] ( /sqlite.html ) to create a [ relational database] ( /databases.html )
140+ with the data then use SQL queries or an
141+ [ object-relational mapper (ORM)] ( /object-relational-mappers-orms.html )
142+ to load the data and perform analysis in pandas.
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