登录
首页 » Python » python数据分析 韩波

python数据分析 韩波

于 2018-09-08 发布 文件大小:171KB
0 373
下载积分: 1 下载次数: 8

代码说明:

  一本python数据分析的优秀资料 《python数据分析》(python data analysis),作者【印尼】Ivan Idris,翻译:韩波。 本人制作的PDF图书,带目录和书签。 作为一种高级程序设计语言,Python凭借其简洁、易读及可扩展性日渐成为程序设计领域备受推崇的语言。同时,Python语言的数据分析功能也逐渐为大众所认可。, 本书是一本介绍如何用Python进行数据分析的学习指南。全书共12章,从Python程序库入门、NumPy数组、matplotlib和pandas开始,陆续介绍了数据加工、数据处理和数据可视化等内容。同时,本书还介绍了信号处理、数据库、文本分析、机器学习、互操作性和性能优化等高级主题。在本书的结尾,还采用3个附录的形式为读者补充了一些重要概念、常用函数以及在线资源等重要内容。, 本书示例丰富、简单易懂,非常适合对Python语言感兴趣或者想要使用Python语言进行数据分析的读者参考阅读。(python data analysis)

文件列表:

3358OS_Code, 0 , 2014-10-24
3358OS_Code\3358OS_01_Code, 0 , 2014-10-24
3358OS_Code\3358OS_01_Code\code1, 0 , 2014-10-24
3358OS_Code\3358OS_01_Code\code1\vectorsum.py, 1148 , 2014-05-04
3358OS_Code\3358OS_02_Code, 0 , 2014-10-24
3358OS_Code\3358OS_02_Code\3358OS_02_Code, 0 , 2014-10-24
3358OS_Code\3358OS_02_Code\3358OS_02_Code\code2, 0 , 2014-10-24
3358OS_Code\3358OS_02_Code\3358OS_02_Code\code2\arrayattributes.py, 587 , 2014-10-24
3358OS_Code\3358OS_02_Code\3358OS_02_Code\code2\arrayattributes2.py, 2016 , 2014-10-24
3358OS_Code\3358OS_02_Code\3358OS_02_Code\code2\arrayconversion.py, 1264 , 2014-10-24
3358OS_Code\3358OS_02_Code\3358OS_02_Code\code2\boolean_indexing.py, 545 , 2014-10-24
3358OS_Code\3358OS_02_Code\3358OS_02_Code\code2\broadcasting.py, 731 , 2014-10-24
3358OS_Code\3358OS_02_Code\3358OS_02_Code\code2\charcodes.py, 399 , 2014-10-24
3358OS_Code\3358OS_02_Code\3358OS_02_Code\code2\copy_view.py, 386 , 2014-10-24
3358OS_Code\3358OS_02_Code\3358OS_02_Code\code2\dtypeattributes.py, 344 , 2014-10-24
3358OS_Code\3358OS_02_Code\3358OS_02_Code\code2\dtypeattributes2.py, 340 , 2014-10-24
3358OS_Code\3358OS_02_Code\3358OS_02_Code\code2\dtypeconstructors.py, 488 , 2014-10-24
3358OS_Code\3358OS_02_Code\3358OS_02_Code\code2\elementselection.py, 396 , 2014-10-24
3358OS_Code\3358OS_02_Code\3358OS_02_Code\code2\fancy.py, 503 , 2014-10-24
3358OS_Code\3358OS_02_Code\3358OS_02_Code\code2\ix.py, 479 , 2014-10-24
3358OS_Code\3358OS_02_Code\3358OS_02_Code\code2\numericaltypes.py, 772 , 2014-10-24
3358OS_Code\3358OS_02_Code\3358OS_02_Code\code2\shapemanipulation.py, 1350 , 2014-10-24
3358OS_Code\3358OS_02_Code\3358OS_02_Code\code2\slicing1d.py, 599 , 2014-10-24
3358OS_Code\3358OS_02_Code\3358OS_02_Code\code2\splitting.py, 1707 , 2014-10-24
3358OS_Code\3358OS_02_Code\3358OS_02_Code\code2\stacking.py, 2817 , 2014-10-24
3358OS_Code\3358OS_03_Code, 0 , 2014-10-24
3358OS_Code\3358OS_03_Code\3358OS_03_Code, 0 , 2014-10-24
3358OS_Code\3358OS_03_Code\3358OS_03_Code\basic_stats.py, 517 , 2014-05-10
3358OS_Code\3358OS_03_Code\3358OS_03_Code\eigenvalues.py, 384 , 2014-05-11
3358OS_Code\3358OS_03_Code\3358OS_03_Code\goog_flutrends.csv, 7549 , 2014-05-11
3358OS_Code\3358OS_03_Code\3358OS_03_Code\headortail.py, 441 , 2014-09-09
3358OS_Code\3358OS_03_Code\3358OS_03_Code\inversion.py, 201 , 2014-09-09
3358OS_Code\3358OS_03_Code\3358OS_03_Code\masked.py, 589 , 2014-10-15
3358OS_Code\3358OS_03_Code\3358OS_03_Code\masked_funcs.py, 778 , 2014-09-09
3358OS_Code\3358OS_03_Code\3358OS_03_Code\mdrtb_2012.csv, 3337 , 2014-05-10
3358OS_Code\3358OS_03_Code\3358OS_03_Code\MLB2008.csv, 7136 , 2014-05-11
3358OS_Code\3358OS_03_Code\3358OS_03_Code\normaldist.py, 304 , 2014-05-11
3358OS_Code\3358OS_03_Code\3358OS_03_Code\normality_test.py, 806 , 2014-05-11
3358OS_Code\3358OS_03_Code\3358OS_03_Code\pkg_check.py, 839 , 2014-05-11
3358OS_Code\3358OS_03_Code\3358OS_03_Code\solution.py, 190 , 2014-05-11
3358OS_Code\3358OS_04_Code, 0 , 2014-10-24
3358OS_Code\3358OS_04_Code\code4, 0 , 2014-10-24
3358OS_Code\3358OS_04_Code\code4\data_aggregation.py, 843 , 2014-05-19
3358OS_Code\3358OS_04_Code\code4\date_handling.py, 757 , 2014-05-30
3358OS_Code\3358OS_04_Code\code4\dest.csv, 47 , 2014-05-19
3358OS_Code\3358OS_04_Code\code4\df_demo.py, 261 , 2014-05-18
3358OS_Code\3358OS_04_Code\code4\join_demo.py, 913 , 2014-05-20
3358OS_Code\3358OS_04_Code\code4\missing_values.py, 498 , 2014-05-21
3358OS_Code\3358OS_04_Code\code4\pivot_demo.py, 493 , 2014-06-11
3358OS_Code\3358OS_04_Code\code4\pkg_check.py, 664 , 2014-06-10
3358OS_Code\3358OS_04_Code\code4\price_straddle.py, 677 , 2014-06-10
3358OS_Code\3358OS_04_Code\code4\query_demo.py, 704 , 2014-05-19
3358OS_Code\3358OS_04_Code\code4\series_demo.py, 621 , 2014-05-18
3358OS_Code\3358OS_04_Code\code4\stats_demo.py, 553 , 2014-05-19
3358OS_Code\3358OS_04_Code\code4\tips.csv, 28 , 2014-05-19
3358OS_Code\3358OS_04_Code\code4\WHO_first9cols.csv, 7776 , 2014-05-18
3358OS_Code\3358OS_05_Code, 0 , 2014-10-24
3358OS_Code\3358OS_05_Code\code5, 0 , 2014-10-24
3358OS_Code\3358OS_05_Code\code5\binary_formats.py, 563 , 2014-05-31
3358OS_Code\3358OS_05_Code\code5\hf5storage.py, 491 , 2014-06-01
3358OS_Code\3358OS_05_Code\code5\json_demo.py, 381 , 2014-06-02
3358OS_Code\3358OS_05_Code\code5\loremIpsum.html, 3623 , 2014-06-07
3358OS_Code\3358OS_05_Code\code5\pd_hdf.py, 597 , 2014-06-01
3358OS_Code\3358OS_05_Code\code5\pd_json.py, 410 , 2014-06-03
3358OS_Code\3358OS_05_Code\code5\pd_xls.py, 320 , 2014-06-01
3358OS_Code\3358OS_05_Code\code5\rss.py, 239 , 2014-06-03
3358OS_Code\3358OS_05_Code\code5\soup_request.py, 1056 , 2014-06-07
3358OS_Code\3358OS_05_Code\code5\writing_csv.py, 277 , 2014-05-31
3358OS_Code\3358OS_06_Code, 0 , 2014-10-24
3358OS_Code\3358OS_06_Code\code6, 0 , 2014-10-24
3358OS_Code\3358OS_06_Code\code6\autocorr_plot.py, 450 , 2014-06-16
3358OS_Code\3358OS_06_Code\code6\basic_plot.py, 137 , 2014-06-14
3358OS_Code\3358OS_06_Code\code6\gpu_transcount.csv, 483 , 2014-06-15
3358OS_Code\3358OS_06_Code\code6\lag_plot.py, 426 , 2014-06-16
3358OS_Code\3358OS_06_Code\code6\legend_annotations.py, 1097 , 2014-06-15
3358OS_Code\3358OS_06_Code\code6\log_plots.py, 373 , 2014-06-14
3358OS_Code\3358OS_06_Code\code6\pd_plotting.py, 478 , 2014-06-15
3358OS_Code\3358OS_06_Code\code6\pkg_check.py, 679 , 2014-06-14
3358OS_Code\3358OS_06_Code\code6\plot_ly.py, 714 , 2014-06-16
3358OS_Code\3358OS_06_Code\code6\scatter_plot.py, 579 , 2014-06-15
3358OS_Code\3358OS_06_Code\code6\three_dimensional.py, 735 , 2014-06-15
3358OS_Code\3358OS_06_Code\code6\transcount.csv, 1123 , 2014-06-14
3358OS_Code\3358OS_06_Code\__MACOSX, 0 , 2014-10-24
3358OS_Code\3358OS_06_Code\__MACOSX\code6, 0 , 2014-10-24
3358OS_Code\3358OS_06_Code\__MACOSX\code6\._gpu_transcount.csv, 120 , 2014-06-15
3358OS_Code\3358OS_06_Code\__MACOSX\code6\._transcount.csv, 120 , 2014-06-14
3358OS_Code\3358OS_07_Code, 0 , 2014-10-24
3358OS_Code\3358OS_07_Code\code7, 0 , 2014-10-24
3358OS_Code\3358OS_07_Code\code7\ar.py, 1350 , 2014-07-05
3358OS_Code\3358OS_07_Code\code7\arma.py, 506 , 2014-07-05
3358OS_Code\3358OS_07_Code\code7\autocorrelation.py, 540 , 2014-07-05
3358OS_Code\3358OS_07_Code\code7\cointegration.py, 695 , 2014-07-04
3358OS_Code\3358OS_07_Code\code7\filtering.py, 609 , 2014-07-06
3358OS_Code\3358OS_07_Code\code7\fourier.py, 898 , 2014-07-06
3358OS_Code\3358OS_07_Code\code7\iterate.dat, 3525 , 2014-07-05
3358OS_Code\3358OS_07_Code\code7\moving_average.py, 461 , 2014-07-04
3358OS_Code\3358OS_07_Code\code7\periodic.py, 1479 , 2014-07-05
3358OS_Code\3358OS_07_Code\code7\pkg_check.py, 678 , 2014-07-03
3358OS_Code\3358OS_07_Code\code7\spectrum.py, 547 , 2014-07-06
3358OS_Code\3358OS_07_Code\code7\window_functions.py, 551 , 2014-07-04

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • 从零开始学Python网络爬虫源代码+教学PPT
    说明:  《从零开始学爬虫》的配套资料(PPT和源码)("Learning Reptiles from Zero" (PPT and Source))
    2019-03-18 22:06:06下载
    积分:1
  • project
    数据挖掘,推荐系统,堆叠降噪自编码器,逻辑回归(Data mining, recommender systems, stack noise reduction, self coder, logic regression)
    2021-01-25 23:58:43下载
    积分:1
  • PCA
    一个用python实现的PCA算法,并且给了简易素材(A PCA algorithm implemented in python, and gave a simple material)
    2020-08-23 14:38:17下载
    积分:1
  • 粗糙集
    粗糙集在进行属性约简时需要求其正域,此为求正域程序(Rough Set for Positive Domain)
    2020-06-19 09:00:06下载
    积分:1
  • 735677
    cfd经典PISO算法的FORTRAN程序()
    2018-05-25 09:08:49下载
    积分:1
  • qb神经网络
    从数据库获取车辆在一段时间内的所有行驶记录的相关数据,确定所需数据为GPS经纬度坐标和驾驶时长等,QB模型采用MDF的思想,其基本思想为:通过平均直接翻转距离函数定义两条轨迹之间的距离,两条轨迹需要具有相同的经纬度点数,具有相同点数的轨迹最大的优点是对轨迹距离成对计算,且相同轨迹之间具有更高的分辨率,对于轨迹聚类的结果有一定的优化。(Retrieved from the database cars all over a period of time, record the related data, determine the required data for the GPS latitude and longitude coordinates, and the driving time, QB model by adopting the idea of MDF, its basic idea is: flip directly by the average distance function definition of the distance between two trajectories, two tracks will have the same latitude and longitude points, and has the biggest advantages of the same points of trajectory track distance calculation in pairs, and has higher resolution, between the same trajectory for trajectory clustering results have certain optimization.)
    2020-06-23 08:00:01下载
    积分:1
  • speech noise reduction
    使用python实现谱减法对语音的降噪功能,代码包括语音的读取、降噪、输出保存(Spectral subtraction speech noise reduction python code)
    2018-06-27 17:22:04下载
    积分:1
  • 0262842
    請用星號( )排列出下列的 p箭 星號 D案,輸入 Y料 ne txt中的第一行為箭 的上下高度(必為奇數),第二行為 D案的總寬度()
    2018-05-28 18:54:24下载
    积分:1
  • OPTICS
    此为利用optics聚类方法剔除风电异常数据后,采用极限学习机验证的代码(optics data mining)
    2017-03-22 19:29:22下载
    积分:1
  • SSTCA
    半监督迁移SSTCA算法实现,matlab代码。包括拉普拉斯图矩阵(Semisupervised Domain Adaptation via Transfer Component Analysis)
    2021-04-23 13:58:48下载
    积分:1
  • 696516资源总数
  • 106914会员总数
  • 0今日下载