I have a Python dataFrame with multiple columns.
LogBlk Page BayFail
0 0 [0, 1, 8, 9]
1 16 [0, 1, 4, 5, 6, 8, 9, 12, 13, 14]
2 32 [0, 1, 4, 5, 6, 8, 9, 12, 13, 14]
3 48 [0, 1, 4, 5, 6, 8, 9, 12, 13, 14]
I want to find BayFails that is associated with LogBlk=0, and Page=0.
df2 = df[ (df['Page'] == 16) & (df['LogBlk'] == 0) ]['BayFail']
This will return [0,1,8,9]
What I want to do is to convert this pandas.series into a list. Does anyone know how to do that?
To convert Pandas DataFrame to List in Python, use the DataFrame. values(). tolist() function.
DataFrame. duplicated() method is used to find duplicate rows in a DataFrame. It returns a boolean series which identifies whether a row is duplicate or unique.
You can use the duplicated() function to find duplicate values in a pandas DataFrame.
pandas.Series, has a tolist method:
In [10]: import pandas as pd
In [11]: s = pd.Series([0,1,8,9], name = 'BayFail')
In [12]: s.tolist()
Out[12]: [0L, 1L, 8L, 9L]
Technical note: In my original answer I said that Series was a subclass of numpy.ndarray and inherited its tolist method. While that's true for Pandas version 0.12 or older, In the soon-to-be-released Pandas version 0.13, Series has been refactored to be a subclass of NDFrame. Series still has a tolist method, but it has no direct relationship to the numpy.ndarray method of the same name.
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