how to convert binary file to pandas dataframe

Question

I use Amazon Sagemaker for model training and prediction. I have a problem with the returned data with predictions. I am trying to convert prediction data to pandas dataframe format.

After the model is deployed:

from sagemaker.serializers import CSVSerializer

xgb_predictor=estimator.deploy(
    initial_instance_count=1,
    instance_type='ml.g4dn.xlarge',
    serializer=CSVSerializer()
)

I made a prediction on the test data:

predictions=xgb_predictor.predict(first_day.to_numpy())

The returned prediction results are in a binary file

predictions

b'2.092024326324463\n10.584211349487305\n18.23127555847168\n2.092024326324463\n8.308058738708496\n32.35516357421875\n4.129155158996582\n7.429899215698242\n55.65376281738281\n116.5504379272461\n1.0734045505523682\n5.29403018951416\n1.0924320220947266\n1.9484598636627197\n5.29403018951416\n2.190509080886841\n2.085641860961914\n2.092024326324463\n7.674410343170166\n2.1198673248291016\n5.293967247009277\n7.088096618652344\n2.092024326324463\n10.410735130310059\n10.36008358001709\n2.092024326324463\n10.565692901611328\n15.495997428894043\n15.61841106414795\n1.0533703565597534\n6.262670993804932\n31.02411460876465\n10.43086051940918\n3.116995096206665\n3.2846100330352783\n108.82835388183594\n26.210166931152344\n1.0658172369003296\n10.55643367767334\n6.245237350463867\n15.951444625854492\n10.195240020751953\n1.0734045505523682\n48.720497131347656\n2.119992256164551\n9.41071605682373\n2.241959810256958\n3.1907501220703125\n10.415051460266113\n1.2154537439346313\n2.13691782951355\n31.1861515045166\n3.0827555656433105\n6.261478424072266\n5.279026985168457\n15.897627830505371\n20.483125686645508\n20.874958038330078\n53.2086296081543\n10.731611251831055\n2.115110397338867\n13.79739761352539\n2.1198673248291016\n26.628803253173828\n10.030998229980469\n15.897627830505371\n5.278475284576416\n45.371158599853516\n2.2791690826416016\n15.58777141571045\n15.947166442871094\n30.88138771057129\n10.388553619384766\n48.22294235229492\n10.565692901611328\n20.808977127075195\n10.388553619384766\n15.910200119018555\n8.252408981323242\n1.109586238861084\n15.58777141571045\n13.718815803527832\n3.1227424144744873\n32.171592712402344\n10.524396896362305\n15.897627830505371\n2.092024326324463\n14.52088737487793\n5.293967247009277\n57.61208724975586\n21.161712646484375\n14.173937797546387\n5.230247974395752\n16.257652282714844

How can I convert prediction data to pandas dataframe?

vagitus · Accepted Answer · 2022-08-02 14:04:44Z

0

you mean this:

import pandas as pd

a = a.decode(encoding="utf-8").split("\n")

df = pd.DataFrame(data=a)
df.head()

answered Aug 2, 2022 at 14:04

vagitus

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