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How do I take multiple lists and put them as different columns in a python dataframe? I tried this solution but had some trouble.
Attempt 1:
- Have three lists, and zip them together and use that
res = zip(lst1,lst2,lst3) - Yields just one column
Attempt 2:
percentile_list = pd.DataFrame({"lst1Tite" : [lst1],
"lst2Tite" : [lst2],
"lst3Tite" : [lst3] },
columns=["lst1Tite","lst1Tite", "lst1Tite"])
- yields either one row by 3 columns (the way above) or if I transpose it is 3 rows and 1 column
How do I get a 100 row (length of each independent list) by 3 column (three lists) pandas dataframe?
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Take multiple lists into dataframe percentile: Questions
How do I calculate percentiles with python/numpy?
1 answers
Is there a convenient way to calculate percentiles for a sequence or single-dimensional numpy array?
I am looking for something similar to Excel"s percentile function.
I looked in NumPy"s statistics reference, and couldn"t find this. All I could find is the median (50th percentile), but not something more specific.
Answer #1
You might be interested in the SciPy Stats package. It has the percentile function you"re after and many other statistical goodies.
percentile() is available in numpy too.
import numpy as np
a = np.array([1,2,3,4,5])
p = np.percentile(a, 50) # return 50th percentile, e.g median.
print p
3.0
This ticket leads me to believe they won"t be integrating percentile() into numpy anytime soon.
