# Take multiple lists into dataframe

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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?

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.

253

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.

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