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32 lines
919 B
Markdown
32 lines
919 B
Markdown
---
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title: "Iteratively Read CSV"
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date: 2020-04-11T21:34:33-04:00
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draft: false
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tags: ["Python"]
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medium_enabled: true
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---
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If you want to analyze a CSV dataset that is larger than the space available in RAM, then you can iteratively process each observation and store/calculate only what you need. There is a way to do this in standard Python as well as the popular library Pandas.
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## Standard Library
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```python
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import csv
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with open('/path/to/data.csv', newline='') as csvfile:
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reader = csv.reader(csvfile, delimeter=',')
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for row in reader:
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for column in row:
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do_something()
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```
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## Pandas
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Pandas is slightly different in where you specify a `chunksize` which is the number of rows per chunk and you get a pandas dataframe with that many rows
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```python
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import pandas as pd
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chunksize = 100
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for chunk in pd.read_csv('/path/to/data.csv', chunksize=chunksize):
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do_something(chunk)
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```
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