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I am familiar with python but new to panda DataFrames. I have a dictionary like this:
a={'b':100,'c':300}
And I would like to convert it to a DataFrame, where b and c are the column names, and the first row is 100,300 (100 is underneath b and 300 is underneath c). I would like a solution that can be generalized to a much longer dictionary, with many more items. Thank you!
946
Method 1: Create DataFrame from Dictionary using default Constructor of pandas. Dataframe class. Method 2: Create DataFrame from Dictionary with user-defined indexes. Method 3: Create DataFrame from simple dictionary i.e dictionary with key and simple value like integer or string value.
from_dict() function. By default, it creates a dataframe with the keys of the dictionary as column names and their respective array-like values as the column values. If you want the dictionary keys to be row indexes instead, pass 'index' to the orient parameter (which is 'columns' by default).
Convert Dictionary To Dataframe With Keys As Columns You can do this by using the orient = 'columns' parameter in the from_dict() method as demonstrated below. This is the default behavior of the from_dict() method. What is this? The dataframe is created with the dictionary keys as rows as shown below.
We can convert a dictionary to a pandas dataframe by using the pd. DataFrame. from_dict() class-method.
Pass the values as a list:
a={'b':[100,],'c':[300,]}
pd.DataFrame(a)
b c
0 100 300
Or if for some reason you don't want to use a list, include an index:
a={'b':100,'c':300}
pd.DataFrame(a, index=['i',])
b c
i 100 300
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