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Transcription Job: Python Programming Lecture - Pandas DataFrames and read_csv
Client: Eagle Web
Transcribed by: Luciah Kemunto
Date: 12/11/2025
Audio Length: 05:16 minutes
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Data frame. Again, all these broadcasting operations are extremely fast. They are backed by the NumPy array and result in a Series.
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You can get quick statistical information using methods like describe, min, max, mean, and median. All work as expected.
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In pandas, you have the concept of a DataFrame with multiple columns and rows. These operations result in just one Series.
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In pandas, you have your DataFrame, and you have your Series, which contain individual numbers. The DataFrame often resorts to Series; some operations return a Series, which can be used in a DataFrame.
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In this case, these operations resulted in a Series. We then immediately used the Series to set the value of a column. That is why understanding Series is so important.
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There are a few more exercises for you here. Complete them to make more sense of it when you are working with it.
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Finally, a quick introduction to reading external data and plotting. We will use the read_csv function from pandas.
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Pandas has several read functions: read_sql, read_excel, read_xml, read_json, and read_html, which can parse an HTML page.[inaudible]
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These functions import data from an external source into a pandas workflow. We will read the BTC market price data.
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The CSV file contains a timestamp and a value. The price data starts from 2017.
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We use the read_csv method to automatically parse the CSV. We will now tune the process to get it right.
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I will show a few customizations for the read_csv function. There are a ton of attributes; you will not remember them all.
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Do not worry; you can always refer to the documentation. The first row of the CSV was considered the column names.
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This file does not have column names. By default, pandas assumes the first line is the header. We will change that assumption.
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We will use header=None. This is one of the attributes we use from the read_csv function.
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Using header=None means do not infer a header from the CSV file. And the columns are... [inaudible]
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