Norm = plt.Normalize(np.min(df), np.max(df))Īx.scatter3D(expiry, df, df, facecolors=colors, s=100)Īx1 = df.G.plot(color='green', grid=True, label='Gold')Īx2 = df.S.plot(color='purple', grid=True, secondary_y=True, label='Silver')Īx. Stats.spearmanr(option,option)ĭata.rolling(3).corr(data)įor i, j in enumerate(data.rolling(3).corr(data)):į'The correlation in sales during months ')Įxpiry = df.apply(lambda x: epoch_converter(x.to_pydatetime(), 'datetime_obj')) Match = re.findall(regex, str) # returns full list of all matche results Left fill s with ASCII '0' digits with total length width # '42' => '00042' Remove trailing whitespace from s # ' hello ' => ' hello' Remove leading whitespace from s # ' hello ' => 'hello ' Replace all tabs with spaces of tabsize integer # 'hello\tworld' => 'hello world' Return true if s ends with any of string tuple s1, s2, and s3Ĭenter s with padding pad of width # 'hi' => 'padpadhipadpad' Return a list of lines in s # 'hello\nworld' => Return list of s split by sep with leftmost maxsplits performed Return list of s split by sep with rightmost maxsplits performed Partition string at last occurrence of sep, return 3-tuple with part before, the sep, and part after # 'hello' => ('hel', 'l', 'o') Partition string at sep and return 3-tuple with part before, the sep itself, and part after # 'hello' => ('he', 'l', 'lo') Return s joined by iterable '123' # 'hello' => '1hello2hello3' Return true if s is titlecased # 'Hello World' => true Return highest index of s2 in s (raise ValueError if not found)Ĭasefold s (aggressive lowercasing for caseless matching) # 'ßorat' => 'ssorat' Replace s2 with s3 in s at most count times, -1 for all instances Example 1 : In this example we can see that by using numpy.dstack () method, we are able to get the combined array. Syntax : numpy.dstack ( (array1, array2)) Return : Return combined array index by index. Return lowest index of s2 in s (but raise ValueError if not found) With the help of numpy.dstack () method, we can get the combined array index by index and store like a stack by using numpy.dstack () method. Index of first occurrence of s2 in s after index i and before index j Remove leading and trailing whitespace from s # ' hello ' => 'hello' Right justify s with total size of width # 'hello' => ' hello' Left justifiy s with total size of width # 'hello' => 'hello ' Return true if s only contains whitespace characters Return integer copies of s concatenated # 'hello' => 'hellohellohello'Ĭenter s with blank padding of width # 'hi' => ' hi '
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