Question 121088 in Redis Question posted in
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Redis – How to Convert Python List with Bytes to Pandas DataFrame?

The input is given as:
rec = [b'1674278797,14.33681', b'1674278798,6.03617', b'1674278799,12.78418']
I want to get a DataFrame like:

df
    timestamp       val
0  1674278797  14.33681
1  1674278798   6.03617
2  1674278799  12.78418

What is the most efficient way? Thanks!

If I can convert rec like
[[1674278797,14.33681], [1674278798,6.03617], [1674278799,12.78418]]
It would be easy for me by calling
df = pd.DataFrame(rec, columns=['timestamp','val'])
But I don’t know how to do the conversion quickly.

btw, I got rec from a Redis list. I can modify the format of each element (for example, b’1674278797,14.33681′ is an element) if necessory.

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2

Answers


  1. 0

    If you can’t directly handle the original input, you can use:

    (pd.Series([x.decode('utf-8') for x in rec])
   .str.split(',', expand=True).convert_dtypes()
   .set_axis(['timestamp', 'val'], axis=1)
)

    Or:

    import io

pd.read_csv(io.StringIO('n'.join([x.decode('utf-8') for x in rec])),
            header=None, names=['timestamp', 'val'])

    Output:

        timestamp       val
0  1674278797  14.33681
1  1674278798   6.03617
2  1674278799  12.78418
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  2. 0

    You can do this in one line:

    pd.DataFrame([x.decode().split(",") for x in rec], columns=["timestamp","val"])

    Returns

        timestamp       val
0  1674278797  14.33681
1  1674278798   6.03617
2  1674278799  12.78418

    If you want to convert the datatypes of the column you can add .astype({"timestamp": "int64", "val": "float64"}) to the end of the line.

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