Hi,
You may find these R/Python comparison-sheets useful in understanding
both languages syntaxes and concepts:
* https://www.datacamp.com/community/tutorials/r-or-python-for-data-analysis
* http://pandas.pydata.org/pandas-docs/stable/comparison_with_r.html
Gaël,
Le 18/06/2017 à 18:02, C W a écrit :
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
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