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I have datarame like the sample data below. I'm trying to convert one row from the dataframe in to a dict like the desired output below. But when I use to_dict I get the indice along with the column value. Does anyone know how to get convert the row to a dict like the desired output? Any tips greatly appreciated.
Sample data:
print(catStr_df[['Bottle Volume (ml)', 'Pack']][:5])
Bottle Volume (ml) Pack
595 750 12
1889 750 12
3616 1000 12
4422 750 12
5022 750 12
Code:
v = catStr_df[catStr_df['Item Number']==34881][['Bottle Volume (ml)', 'Pack']]\
.drop_duplicates(keep='first').to_dict()
v
Output:
{'Bottle Volume (ml)': {9534: 1000}, 'Pack': {9534: 12}}
Desired output:
{'Bottle Volume (ml)': 1000, 'Pack': 12}
804
DataFrame to dict by row index When we have a DataFrame with row indexes and if we need to convert the data of each row from DataFrame to dict , we can use the index parameter of the DataFrame. to_dict() function. It returns a list of dictionary objects. A dict is created for each row.
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).
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".
When we have a DataFrame with row indexes and if we need to convert the data of each row from DataFrame to dict, we can use the index parameter of the DataFrame.to_dict () function. It returns a list of dictionary objects. A dict is created for each row. Where the key is a row index, and the value is dict of column label and data.
Pandas is one of those packages and makes importing and analyzing data much easier. Pandas .to_dict() method is used to convert a dataframe into a dictionary of series or list like data type depending on orient parameter. Syntax: DataFrame.to_dict(orient=’dict’, into=)
It is a case when we have DataFrame, which needs to be converted into the dictionary object such that column label should be the keys in the dictionary, and all the columns’ data should be added into the resultant dict as a list of values against each key. In that case, we can use 'list' parameter of the DataFrame.to_dict () function.
Pandas .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).
Try adding .to_dict('records')[0] to the row you want
catStr_df[catStr_df['Item Number']==34881].to_dict('records')[0]
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