為什么80%的碼農都做不了架構師？>>> ??

import pandas import numpy# 通過傳遞一個 numpyarray，時間索引以及列標簽來創建一個DataFrame： dates = pandas.date_range("20180509", periods=6) df = pandas.DataFrame(numpy.random.randn(6, 4), index=dates, columns=list('ABCD')) print("時間索引以及列標簽來創建一個DataFrame:", df, sep="\n")# 查看DataFrame中頭部和尾部的行 print("頭部行: ", df.head(), sep="\n") # 不給定head()參數時，默認除最后一行都是頭部 print("尾部行: ", df.tail(), sep="\n") # 不給定tail()參數時，默認除第一行都是尾部 print("頭部行第一行: ", df.head(1), sep="\n") print("尾部行最后一行: ", df.tail(1), sep="\n")# 顯示索引、列和底層的numpy數據 print("索引：", df.index, sep="\n") print("列：", df.columns, sep="\n") print("值：", df.values, sep="\n")# describe()函數對于數據的快速統計匯總 print("數據統計：", df.describe(), sep="\n")# 對數據的轉置 print("對數據的轉置: ", df.T, sep="\n")# 按軸進行排序 print("按軸進行排序: ", df.sort_index(axis=0, ascending=False), sep="\n") # ascending 是否自增# 按值進行排序 print("按值進行排序: ", df.sort_values(by='B'), sep="\n") "E:\Python 3.6.2\python.exe" F:/PycharmProjects/test.py 時間索引以及列標簽來創建一個DataFrame:A B C D 2018-05-09 -1.900068 -0.208794 -0.523035 1.240455 2018-05-10 1.512279 -2.283494 0.608609 1.027053 2018-05-11 -3.320670 -0.260807 0.508715 0.662909 2018-05-12 0.338343 -1.735734 1.500790 -0.959845 2018-05-13 1.990765 0.214486 -1.244937 -0.258515 2018-05-14 -1.044454 0.360775 -0.657407 -0.593493 頭部行: A B C D 2018-05-09 -1.900068 -0.208794 -0.523035 1.240455 2018-05-10 1.512279 -2.283494 0.608609 1.027053 2018-05-11 -3.320670 -0.260807 0.508715 0.662909 2018-05-12 0.338343 -1.735734 1.500790 -0.959845 2018-05-13 1.990765 0.214486 -1.244937 -0.258515 尾部行: A B C D 2018-05-10 1.512279 -2.283494 0.608609 1.027053 2018-05-11 -3.320670 -0.260807 0.508715 0.662909 2018-05-12 0.338343 -1.735734 1.500790 -0.959845 2018-05-13 1.990765 0.214486 -1.244937 -0.258515 2018-05-14 -1.044454 0.360775 -0.657407 -0.593493 頭部行第一行: A B C D 2018-05-09 -1.900068 -0.208794 -0.523035 1.240455 尾部行最后一行: A B C D 2018-05-14 -1.044454 0.360775 -0.657407 -0.593493 索引： DatetimeIndex(['2018-05-09', '2018-05-10', '2018-05-11', '2018-05-12','2018-05-13', '2018-05-14'],dtype='datetime64[ns]', freq='D') 列： Index(['A', 'B', 'C', 'D'], dtype='object') 值： [[-1.90006837 -0.20879388 -0.52303491 1.24045481][ 1.51227925 -2.28349377 0.60860861 1.02705302][-3.32067045 -0.26080686 0.50871488 0.6629095 ][ 0.33834299 -1.73573353 1.5007895 -0.95984505][ 1.99076464 0.21448643 -1.24493715 -0.25851535][-1.04445367 0.36077537 -0.65740657 -0.59349347]] 數據統計：A B C D count 6.000000 6.000000 6.000000 6.000000 mean -0.403968 -0.652261 0.032122 0.186427 std 2.054919 1.091991 1.013014 0.912672 min -3.320670 -2.283494 -1.244937 -0.959845 25% -1.686165 -1.367002 -0.623814 -0.509749 50% -0.353055 -0.234800 -0.007160 0.202197 75% 1.218795 0.108666 0.583635 0.936017 max 1.990765 0.360775 1.500790 1.240455 對數據的轉置: 2018-05-09 2018-05-10 2018-05-11 2018-05-12 2018-05-13 2018-05-14 A -1.900068 1.512279 -3.320670 0.338343 1.990765 -1.044454 B -0.208794 -2.283494 -0.260807 -1.735734 0.214486 0.360775 C -0.523035 0.608609 0.508715 1.500790 -1.244937 -0.657407 D 1.240455 1.027053 0.662909 -0.959845 -0.258515 -0.593493 按軸進行排序: A B C D 2018-05-14 -1.044454 0.360775 -0.657407 -0.593493 2018-05-13 1.990765 0.214486 -1.244937 -0.258515 2018-05-12 0.338343 -1.735734 1.500790 -0.959845 2018-05-11 -3.320670 -0.260807 0.508715 0.662909 2018-05-10 1.512279 -2.283494 0.608609 1.027053 2018-05-09 -1.900068 -0.208794 -0.523035 1.240455 按值進行排序: A B C D 2018-05-10 1.512279 -2.283494 0.608609 1.027053 2018-05-12 0.338343 -1.735734 1.500790 -0.959845 2018-05-11 -3.320670 -0.260807 0.508715 0.662909 2018-05-09 -1.900068 -0.208794 -0.523035 1.240455 2018-05-13 1.990765 0.214486 -1.244937 -0.258515 2018-05-14 -1.044454 0.360775 -0.657407 -0.593493Process finished with exit code 0

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