Hi, along with all the great tips you received, perhaps you may find this useful:
http://www.cert.org/flocon/2011/matlab-python-xref.pdf I know is not on-topic with your question, but I found it very useful when I start to use python (coming from R) So I thought it was worth to post it here. It is very old but those basic functions are pretty stable. The python code assumes a: from numpy import * which others already explained you why is good practice to avoid it, —Massimo. > On Jun 18, 2017, at 12:02 PM, C W <tmrs...@gmail.com> wrote: > > Dear Scikit-learn, > > What are some good ways and resources to learn Python for data analysis? > > I am extremely frustrated using this thing. Everything comes after a dot! Why > would you type the sam thing at the beginning of every line. It's not > efficient. > > code 1: > y_sin = np.sin(x) > y_cos = np.cos(x) > > I know you can import the entire package without the "as np", but I see > np.something as the standard. Why? > > Code 2: > model = LogisticRegression() > model.fit(X_train, y_train) > model.score(X_test, y_test) > > In R, everything is saved to a variable. In the code above, what if I > accidentally ran model.fit(), I would not know. > > Code 3: > from sklearn import linear_model > reg = linear_model.Ridge (alpha = .5) > reg.fit ([[0, 0], [0, 0], [1, 1]], [0, .1, 1]) > > In the code above, sklearn > linear_model > Ridge, one lives inside the > other, it feels that there are multiple layer, how deep do I have to dig in? > > Can someone explain the mentality behind this setup? > > Thank you very much! > > M > _______________________________________________ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn _______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
