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pandas.Seriesclass pandas.Series(data=None, index=None, dtype=None, name=None, copy=None, fastpath=False)import pandas as pdfruits = ['apples', 'oranges', 'cherries', 'pears']quantities1 = [20, 33, 52, 10]quantities2 = [14, 23, 45, 36]S1 = pd.Series(quantities1, index = fruits)S2 = pd.Series(quantities2, index = fruits)S * S1apples 400 oranges 1089 cherries 2704 pears 100 dtype: int64import pand..
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SUBPLOTSmatplotlib.pyplot.subplotsmatplotlib.pyplot.subplots(nrows=1, ncols=1, *, sharex=False, sharey=False, squeeze=True, width_ratios=None, height_ratios=None, subplot_kw=None, gridspec_kw=None, **fig_kw)import numpy as npimport matplotlib.pyplot as pltfig, ax = plt.subplots(nrows=2, ncols=2)plt.show()import numpy as npimport matplotlib.pyplot as pltfig, (ax1, ax2) = plt.subplots(nrows=2, nco..
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개요lineimport matplotlib.pyplot as pltplt.plot([-1,-4.5,16,23])plt.show() pointimport matplotlib.pyplot as pltplt.plot([-1,-4.5,16,23], "ob")plt.show()Aapoint + line ( temp )import matplotlib.pyplot as pltdays = list(range(1,9))celsius_min = [19.6, 24.1, 26.7, 28.3, 27.5, 30.5, 32.8, 33.1]celsius_max = [24.8, 28.9, 31.3, 33.0, 34.9, 35.6, 38.4, 39.2]fig, ax = plt.subplots()ax.set(xlabel = "Day", ..
NUMPY ARRAYS: CONCATENATING, FLATTENING AND ADDING DIMENSIONS Flatten VS Ravel FLATTEN import numpy as npA = np.array([[[ 0, 1], [ 2, 3], [ 4, 5], [ 6, 7]], [[ 8, 9], [10, 11], [12, 13], [14, 15]], [[16, 17], [18, 19], [20, 21], [2..
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numpy ones & zeros & ones_like & zeros_likenumpy.ones(shape, dtype=None, order='C', *, like=None)np.ones((5,),dtype = int)array([1, 1, 1, 1, 1])f = np.ones((2,3))farray([[1., 1., 1.], [1., 1., 1.]]) numpy.zeros(shape, dtype=float, order='C', *, like=None)# 2행 4열a = np.zeros((2,4), dtype = int)aarray([[0, 0, 0, 0], [0, 0, 0, 0]]) numpy.ones_like(a, dtype=None, order='K', subok=True, shape=None)ar..
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기본 개념 리스트는 배열(벡터)을 가지고 있지 않아서 곱하기나 나누기 같은 연산을 하지 못함 ⇒ 차원이 없다 그냥 요소를 가지고 있는 리스트일 뿐배열로 바꿔주기 위해서는 numpy 사용 (array로 변환)배열로 바꿔주면(np.array) 모든 연산 가능! numpy.arange()numpy.arange([start, ]stop, [step, ]dtype=None, *, like=None)return : ndarray(n차원 디멘션(차원)으로 반환해줌)'''dtype(start + step) - dtype(start) and not step.'''np.arange(0, 5, 0.5, dtype=int)array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0])np.arange(0, 5, 0.5)a..
