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For example, I have DataFrame now as
id score1 score2 score3 score4 score5 1 0.000000 0.108659 0.000000 0.078597 1 2 0.053238 0.308253 0.286353 0.446433 1 3 0.000000 0.083979 0.808983 0.233052 1 I want to convert it as
id scoreDict 1 {'1': 0, '2': 0.1086, ...} 2 {...} 3 {...} Anyway to do that?
747
First, search for the table header and split on spaces to define a list. Second, search for the virtual drive with "number/number" and split on spaces to define the second list. However, 'Size' will need to be special as it will need to ignore the space between number and "TB".
to_dict() method is used to convert a dataframe into a dictionary of series or list like data type depending on orient parameter. Parameters: orient: String value, ('dict', 'list', 'series', 'split', 'records', 'index') Defines which dtype to convert Columns(series into).
import pandas as pd # your df # ========================= print(df) id score1 score2 score3 score4 score5 0 1 0.0000 0.1087 0.0000 0.0786 1 1 2 0.0532 0.3083 0.2864 0.4464 1 2 3 0.0000 0.0840 0.8090 0.2331 1 # to_dict # ========================= df.to_dict(orient='records') Out[318]: [{'id': 1.0, 'score1': 0.0, 'score2': 0.10865899999999999, 'score3': 0.0, 'score4': 0.078597, 'score5': 1.0}, {'id': 2.0, 'score1': 0.053238000000000001, 'score2': 0.308253, 'score3': 0.28635300000000002, 'score4': 0.44643299999999997, 'score5': 1.0}, {'id': 3.0, 'score1': 0.0, 'score2': 0.083978999999999998, 'score3': 0.80898300000000001, 'score4': 0.23305200000000001, 'score5': 1.0}] If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
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