Patreon:
https://www.patreon.com/kfsoft* 該影片為第2版,加入/重製了約1小時之新內容,擴展了Column部分
* This is 2nd edition of this tutorial, it expands the column part: filter(), replace(), apply(), applymap() & map()
Doing data science with python:
1) Pandas basics: Series & DataFrame
2) Tips dataset, SQL equivalent pandas methods
Files:
https://github.com/learn10kYear/learn-pandas/tree/master/lab1Cheat sheet from pandas.pydata.org:
https://pandas.pydata.org/Pandas_Cheat_Sheet.pdf00:00 Intro
00:34 PART1 - Pandas basics: Tubular data, Series & DataFrame
02:27 Install & import pandas
04:22 Series: 1d-list structure, with index
10:28 DataFrame: 2d-table structure, with index & columns
25:19 DataFrame - col: dot notation, fancy index, filter() by columns
30:16 DataFrame - col: add col
32:57 DataFrame - col: filter() - col name / index name
38:15 DataFrame - col: mean(), medium(), max(), idxmax(), update
42:54 DataFrame - col: update data
55:23 DataFrame - col: common str funcs
01:06:22 DataFrame - col: replace func - series.replace()
01:15:16 DataFrame - col: replace func - df.replace()
01:19:32 DataFrame - col: 3 update funcs - Call any functions on each cell / col / row to update data
01:20:34 DataFrame - col: 1a) apply() for series's items & df's columns
01:27:52 DataFrame - col: 1b) apply() - function arguments, lambda
01:32:24 DataFrame - col: 1c) apply() - axis=columns/index
01:35:32 DataFrame - col: 1d) apply() - result_type (for multi-values results, AND df.apply())
01:40:08 DataFrame - col: 2) applymap() - df only, on every element of a df
01:42:03 DataFrame - col: 3) map() - series only, on every element of a series, accept dict & func
01:45:50 DataFrame - col: drop() to a col
01:48:27 DataFrame - row: slice, filter() by rows
01:52:56 DataFrame - row: 2 indexers - LOC (label), ILOC (position)
01:53:45 DataFrame - row: loc (label) indexer - df.loc[row, col]
02:00:13 DataFrame - row: iloc (position) indexer - df.iloc[row, col]
02:04:32 DataFrame - row: use boolean mask to retrieve records
02:08:16 DataFrame - row: query() to retrieve records
02:12:46 DataFrame - row: missing values handling, isna(), isnull(), notna(), notnull(), fillna()
02:15:33 DataFrame - row: groupby() and agg()
02:18:23 DataFrame - row: groupby multiple columns VS pivot_table()
02:23:04 DataFrame - row: sort_values(), by multiple columns with different directions
02:25:11 PART 2 - Tips dataset: use pandas on a dataset
02:26:58 Tips Dataset: import packages & read tips dataset
02:31:52 SQL equivalent - SELECT: fancy index, filter(), loc, iloc
02:35:24 SQL equivalent - SELECT: with new column
02:36:33 SQL equivalent - WHERE: boolean mask, query()
02:38:12 SQL equivalent - WHERE multiple conditions: and, or
02:41:10 SQL equivalent - NULL handling: isnull(), isna(), notna()
02:42:23 SQL equivalent - GROUPBY: single field groupby, and apply agg functions
02:46:11 SQL equivalent - GROUPBY: multiple fields groupby
02:47:19 SQL equivalent - JOIN: inner (intersection) / outer (union) - on='column', how='inner/outer'
02:50:29 SQL equivalent - JOIN: left (keep LHS) / right (keep RHS) - on='column', how='left/right'
02:52:05 SQL equivalent - UNION: pd.concat([ds1, ds2]).drop_doplicates()
02:53:17 SQL equivalent - UPDATE: df.loc, map()
02:56:04 SQL equivalent - DELETE: boolean mask method
02:59:01 Save DataFrame to a file
03:00:25 Plot graph - df.plot()
03:00:56 Summary
Python入門:第1課 - PyCharm + Data Types
https://youtu.be/s9toTBXQSPEPython入門:第2課 - Python containers (1): List, Tuple
https://youtu.be/7hm0zHgEGZ4Python入門:第3課 - Python containers (2): Dictionary & Set
https://youtu.be/7Jvfd6qFLzUPython入門:第4課 - If-Else, Looping, Try-except
https://youtu.be/sXdh5L5rcX0Python入門:第5課 - Function + File
https://youtu.be/rk8kU3no5NoPython入門:第6課 - Class and Object
https://youtu.be/HPb0Lg3FQfMPython入門:第7課 - URL, JSON, Sqlite
https://youtu.be/93lOZTxJtrsPython初級:第15課 - Web Scraping 靜態網頁抓取
https://youtu.be/_LRfuctPLdsPython初級:第16課 - Web Scraping 動態網頁抓取
https://youtu.be/lXwgSweHf5QPython初級:第17課 - Pygame貪食蛇遊戲
https://youtu.be/kaDEcF5LTWUPython入門 - 數據科學 - Jupyter Lab & Notebook 安裝+入門教程
https://youtu.be/niWD8kxgpH0Python入門 - 數據科學 - Anaconda + PyCharm 安裝
https://youtu.be/H4ihRvtdY7MPython初級 - 數據科學 - Numpy入門
https://youtu.be/t7ygnafk760Python初級 - 數據科學 - Pandas入門
https://youtu.be/ZYjhM7J9eFQPython初級 - 數據科學 - Pandas入門 (第二版 更新column部分)
https://youtu.be/w76oa7YzvkYPython初級 - 數據科學 - Pandas時間 + 圖表
https://youtu.be/jrd8shHEVFQPython初級 - 數據科學 - Pandas類別 + 樣式
https://youtu.be/4ntwbAWnKbgDatabase初級:SQL入門
https://youtu.be/OtM74u3Fbw0Database初級:JOIN連接
https://youtu.be/tpDvgr7qHswDatabase初級:MongoDB入門
https://youtu.be/XTqW3oOt3PsPython初級 - 機器學習 - Scikit-learn 入門
https://youtu.be/3m8Bb01uNNEPython初級 - 機器學習 - Scikit-learn - Regression 回歸
https://youtu.be/QyYZT8o-f3UPython初級 - 機器學習 - Scikit-learn - Classification 分類
https://youtu.be/JKn0OoHSoRoPython初級 - 機器學習 - Scikit-learn - Clustering 聚類+降維
https://youtu.be/UgXyK-k-CgMhttps://kfsoft.infoAbout the Site 🌐
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