Shiyang Feng ShiyangFeng
ShiyangFeng
/ logistic_sklearn.ipynb
Created
February 17, 2017 20:26
— forked from justmarkham/logistic_sklearn.ipynb
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ShiyangFeng
/ logistic_sklearn.ipynb
Created
February 17, 2017 20:26
— forked from justmarkham/logistic_sklearn.ipynb
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ShiyangFeng
/ gist:247152552f50fc628a6359666c44530e
Created
February 5, 2017 21:02
— forked from why-not/gist:4582705
Pandas recipe. I find pandas indexing counter intuitive, perhaps my intuitions were shaped by many years in the imperative world. I am collecting some recipes to do things quickly in pandas & to jog my memory.
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| """quick way to create a data frame to try things out""" | |
| df = pd.DataFrame(np.random.randn(5, 4), columns=['a', 'b', 'c', 'd']) | |
| df['A'] """ will bring out a col """ df.ix[0] """will bring out a row, #0 in this case""" | |
| """to get an array from a data frame or a series use values, note it is not a function here, so no parans ()""" | |
| point = df_allpoints[df_allpoints['names'] == given_point] # extract one point row. | |
| point = point['desc'].values[0] # get its descriptor in array form. |
ShiyangFeng
/ gist:198aad5646068e58e213c0e6180814b6
Created
February 5, 2017 21:02
— forked from why-not/gist:4582705
Pandas recipe. I find pandas indexing counter intuitive, perhaps my intuitions were shaped by many years in the imperative world. I am collecting some recipes to do things quickly in pandas & to jog my memory.
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| """quick way to create a data frame to try things out""" | |
| df = pd.DataFrame(np.random.randn(5, 4), columns=['a', 'b', 'c', 'd']) | |
| df['A'] """ will bring out a col """ df.ix[0] """will bring out a row, #0 in this case""" | |
| """to get an array from a data frame or a series use values, note it is not a function here, so no parans ()""" | |
| point = df_allpoints[df_allpoints['names'] == given_point] # extract one point row. | |
| point = point['desc'].values[0] # get its descriptor in array form. |