{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "df = pd.read_csv(\"../day9/demo.csv\")" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
MailboxNotes IDTeam LeaderGithub accountSession 1Unnamed: 5Session 2Unnamed: 7Session 3Unnamed: 9Session 4Unnamed: 11Session 5Unnamed: 13Session 6Unnamed: 15Session 7Unnamed: 17Session 8
0pdlzhang@cn.ibm.comPing DZ Zhang/China/IBMCheng ChenYYIncorrectYNYNYNYNaNNNaNYNaNY
1yananzh@cn.ibm.comYa Nan YN Zhuang/China/IBMCheng ChenYYDoneYDoneYDoneYDoneYNaNN 项目会议冲突NaNYNaNY
2lizhjdl@cn.ibm.comZhen Jie DL Li/China/IBMCheng ChenYYDoneN shiftDoneN shiftDoneN shiftDoneN shiftNaNN shiftNaNN shiftNaNN shift
3yuanlyy@cn.ibm.comYuan Yuan YB Li/China/IBMCheng ChenYYDoneYIncorrectYDoneN 项目会议冲突IncorrectYNaNYNaNNNaNY
4shuyang@cn.ibm.comYang Shu/China/IBMCheng ChenYYDoneYDoneYDoneYDoneYNaNYNaNYNaNN会议冲突
5zhouyldl@cn.ibm.comYi Li AZ Zhou/China/IBMCheng ChenYYDoneYDoneYDoneN 项目会议冲突DoneYNaNYNaNYNaNY
6lizidl@cn.ibm.comZi DL Li/China/IBMCheng ChenYYDoneYDoneYDoneYDoneYNaNYNaNYNaNY
7wangyih@cn.ibm.comYi Han HY Wang/China/IBMCheng ChenYYDoneYDoneYDoneYIncorrectYNaNYNaNYNaNY
8guoqq@cn.ibm.comQian Qian QQ Guo/China/IBMYin LuYYDoneYDoneYDoneYDoneYNaNYNaNYNaNY
9shangx@cn.ibm.comXia Shang/China/IBMYin LuYYDoneYDoneYDoneYDoneYNaNYNaNYNaNY
10xinzhdl@cn.ibm.comXin RZ Zhang/China/IBMYin LuYYDoneYDoneYDoneYIncorrectYNaNYNaNYNaNY
11ymying@cn.ibm.comMiao Ying MY Yang/China/IBMYin LuYYDoneYDoneYDoneYDoneYNaNYNaNYNaNY
12jmhjiang@cn.ibm.comMing Hui LJ Jiang/China/IBMYin LuY迟到Done迟到DoneYIncorrectYIncorrectYNaNYNaNYNaNY
13xiaoywdl@cn.ibm.comXiao Yan XY Wang/China/IBMYin LuYYDoneYDoneYDoneYIncorrectYNaNN有其他会议NaNYNaNY
14wpeter@cn.ibm.comPeter Y Wang/China/IBMYin LuYYDoneYNNNN跟客户有会NNNaNN跟客户有会NaNYNaNN
15issczli@cn.ibm.comLi T Zhang/China/IBMHeng CaiYYDoneYNNNNNYNaNYNaNYNaNY
16zoujin@cn.ibm.comJin Zou/China/IBMHeng CaiYYDoneYDoneYDoneN 项目会议冲突IncorrectYNaNYNaNYNaNN会议冲突
17fygao@cn.ibm.comFang Yue FY Gao/China/IBMHeng CaiYYDoneN 项目会议冲突DoneYDoneYDoneYNaNYNaNYNaNY
18dllsyliu@cn.ibm.comSi Yang IL Liu/China/IBMHeng CaiYYDoneYNYIncorrectYNYNaNYNaNYNaNY
19dlwjia@cn.ibm.comJia AW Wang/China/IBMHeng CaiYYDoneYDoneYDoneYDoneYNaNYNaNYNaNY
20ssliu@cn.ibm.comSheng Heng Liu/China/IBMHeng CaiY早退DoneYDoneYDoneN见客户IncorrectYNaNN跟客户有会议NaNYNaNN跟客户有会议
21fenghao@cn.ibm.comfenghao@cn.ibm.comHeng CaiYNA(从第六节课来的插班生)DoneNaNNNaNNNaNNNaNNaNYNaNYNaNY
22xhongdl@cn.ibm.comHong XH Xiao/China/IBMWu DanYYDoneYDoneYDoneYIncorrectYNaNYNaNYNaNY
23haojiedl@cn.ibm.comJie EH Hao/China/IBMWu DanYYDoneYDoneNDoneYNYNaNYNaNYNaNY
24mumeilun@cn.ibm.comMei Lun IM Mu/China/IBMWu DanYYDoneYDoneNDoneYDoneYNaNYNaNYNaNY
25jinglil@cn.ibm.comJing Li Liu/China/IBMWu DanYYDoneYDoneYDoneYDoneYNaNYNaNYNaNY
26caijm@cn.ibm.comJin Ming JM Cai/China/IBMWu DanYYDoneYDoneYDoneYDoneYNaNYNaNYNaNY
27lidannie@cn.ibm.comLi Dan N Nie/China/IBMWu DanYYDoneYDoneYDoneYDoneYNaNYNaNYNaNY
28dongmhtu@cn.ibm.comMei Hua TU Dong/China/IBMWu DanYYDoneYDoneYIncorrectYIncorrectYNaNYNaNYNaNY
29zhangwyi@cn.ibm.comWei Yi WY Zhang/China/IBMWu DanYYDoneYDoneYDoneYDoneYNaNYNaNYNaNY
30zhanglp@cn.ibm.comLian Ping Zhang/China/IBMHeng Cai（四年经验（以后答疑））NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
\n", "
" ], "text/plain": [ " Mailbox Notes ID Team Leader \\\n", "0 pdlzhang@cn.ibm.com Ping DZ Zhang/China/IBM Cheng Chen \n", "1 yananzh@cn.ibm.com Ya Nan YN Zhuang/China/IBM Cheng Chen \n", "2 lizhjdl@cn.ibm.com Zhen Jie DL Li/China/IBM Cheng Chen \n", "3 yuanlyy@cn.ibm.com Yuan Yuan YB Li/China/IBM Cheng Chen \n", "4 shuyang@cn.ibm.com Yang Shu/China/IBM Cheng Chen \n", "5 zhouyldl@cn.ibm.com Yi Li AZ Zhou/China/IBM Cheng Chen \n", "6 lizidl@cn.ibm.com Zi DL Li/China/IBM Cheng Chen \n", "7 wangyih@cn.ibm.com Yi Han HY Wang/China/IBM Cheng Chen \n", "8 guoqq@cn.ibm.com Qian Qian QQ Guo/China/IBM Yin Lu \n", "9 shangx@cn.ibm.com Xia Shang/China/IBM Yin Lu \n", "10 xinzhdl@cn.ibm.com Xin RZ Zhang/China/IBM Yin Lu \n", "11 ymying@cn.ibm.com Miao Ying MY Yang/China/IBM Yin Lu \n", "12 jmhjiang@cn.ibm.com Ming Hui LJ Jiang/China/IBM Yin Lu \n", "13 xiaoywdl@cn.ibm.com Xiao Yan XY Wang/China/IBM Yin Lu \n", "14 wpeter@cn.ibm.com Peter Y Wang/China/IBM Yin Lu \n", "15 issczli@cn.ibm.com Li T Zhang/China/IBM Heng Cai \n", "16 zoujin@cn.ibm.com Jin Zou/China/IBM Heng Cai \n", "17 fygao@cn.ibm.com Fang Yue FY Gao/China/IBM Heng Cai \n", "18 dllsyliu@cn.ibm.com Si Yang IL Liu/China/IBM Heng Cai \n", "19 dlwjia@cn.ibm.com Jia AW Wang/China/IBM Heng Cai \n", "20 ssliu@cn.ibm.com Sheng Heng Liu/China/IBM Heng Cai \n", "21 fenghao@cn.ibm.com fenghao@cn.ibm.com Heng Cai \n", "22 xhongdl@cn.ibm.com Hong XH Xiao/China/IBM Wu Dan \n", "23 haojiedl@cn.ibm.com Jie EH Hao/China/IBM Wu Dan \n", "24 mumeilun@cn.ibm.com Mei Lun IM Mu/China/IBM Wu Dan \n", "25 jinglil@cn.ibm.com Jing Li Liu/China/IBM Wu Dan \n", "26 caijm@cn.ibm.com Jin Ming JM Cai/China/IBM Wu Dan \n", "27 lidannie@cn.ibm.com Li Dan N Nie/China/IBM Wu Dan \n", "28 dongmhtu@cn.ibm.com Mei Hua TU Dong/China/IBM Wu Dan \n", "29 zhangwyi@cn.ibm.com Wei Yi WY Zhang/China/IBM Wu Dan \n", "30 zhanglp@cn.ibm.com Lian Ping Zhang/China/IBM Heng Cai \n", "\n", " Github account Session 1 Unnamed: 5 Session 2 Unnamed: 7 Session 3 \\\n", "0 Y Y Incorrect Y N Y \n", "1 Y Y Done Y Done Y \n", "2 Y Y Done N shift Done N shift \n", "3 Y Y Done Y Incorrect Y \n", "4 Y Y Done Y Done Y \n", "5 Y Y Done Y Done Y \n", "6 Y Y Done Y Done Y \n", "7 Y Y Done Y Done Y \n", "8 Y Y Done Y Done Y \n", "9 Y Y Done Y Done Y \n", "10 Y Y Done Y Done Y \n", "11 Y Y Done Y Done Y \n", "12 Y 迟到 Done 迟到 Done Y \n", "13 Y Y Done Y Done Y \n", "14 Y Y Done Y N N \n", "15 Y Y Done Y N N \n", "16 Y Y Done Y Done Y \n", "17 Y Y Done N 项目会议冲突 Done Y \n", "18 Y Y Done Y N Y \n", "19 Y Y Done Y Done Y \n", "20 Y 早退 Done Y Done Y \n", "21 Y NA(从第六节课来的插班生) Done NaN N NaN \n", "22 Y Y Done Y Done Y \n", "23 Y Y Done Y Done N \n", "24 Y Y Done Y Done N \n", "25 Y Y Done Y Done Y \n", "26 Y Y Done Y Done Y \n", "27 Y Y Done Y Done Y \n", "28 Y Y Done Y Done Y \n", "29 Y Y Done Y Done Y \n", "30 （四年经验（以后答疑）） NaN NaN \n", "\n", " Unnamed: 9 Session 4 Unnamed: 11 Session 5 Unnamed: 13 Session 6 \\\n", "0 N Y N Y NaN N \n", "1 Done Y Done Y NaN N 项目会议冲突 \n", "2 Done N shift Done N shift NaN N shift \n", "3 Done N 项目会议冲突 Incorrect Y NaN Y \n", "4 Done Y Done Y NaN Y \n", "5 Done N 项目会议冲突 Done Y NaN Y \n", "6 Done Y Done Y NaN Y \n", "7 Done Y Incorrect Y NaN Y \n", "8 Done Y Done Y NaN Y \n", "9 Done Y Done Y NaN Y \n", "10 Done Y Incorrect Y NaN Y \n", "11 Done Y Done Y NaN Y \n", "12 Incorrect Y Incorrect Y NaN Y \n", "13 Done Y Incorrect Y NaN N有其他会议 \n", "14 N N跟客户有会 N N NaN N跟客户有会 \n", "15 N N N Y NaN Y \n", "16 Done N 项目会议冲突 Incorrect Y NaN Y \n", "17 Done Y Done Y NaN Y \n", "18 Incorrect Y N Y NaN Y \n", "19 Done Y Done Y NaN Y \n", "20 Done N见客户 Incorrect Y NaN N跟客户有会议 \n", "21 N NaN N NaN NaN Y \n", "22 Done Y Incorrect Y NaN Y \n", "23 Done Y N Y NaN Y \n", "24 Done Y Done Y NaN Y \n", "25 Done Y Done Y NaN Y \n", "26 Done Y Done Y NaN Y \n", "27 Done Y Done Y NaN Y \n", "28 Incorrect Y Incorrect Y NaN Y \n", "29 Done Y Done Y NaN Y \n", "30 NaN NaN NaN NaN NaN NaN \n", "\n", " Unnamed: 15 Session 7 Unnamed: 17 Session 8 \n", "0 NaN Y NaN Y \n", "1 NaN Y NaN Y \n", "2 NaN N shift NaN N shift \n", "3 NaN N NaN Y \n", "4 NaN Y NaN N会议冲突 \n", "5 NaN Y NaN Y \n", "6 NaN Y NaN Y \n", "7 NaN Y NaN Y \n", "8 NaN Y NaN Y \n", "9 NaN Y NaN Y \n", "10 NaN Y NaN Y \n", "11 NaN Y NaN Y \n", "12 NaN Y NaN Y \n", "13 NaN Y NaN Y \n", "14 NaN Y NaN N \n", "15 NaN Y NaN Y \n", "16 NaN Y NaN N会议冲突 \n", "17 NaN Y NaN Y \n", "18 NaN Y NaN Y \n", "19 NaN Y NaN Y \n", "20 NaN Y NaN N跟客户有会议 \n", "21 NaN Y NaN Y \n", "22 NaN Y NaN Y \n", "23 NaN Y NaN Y \n", "24 NaN Y NaN Y \n", "25 NaN Y NaN Y \n", "26 NaN Y NaN Y \n", "27 NaN Y NaN Y \n", "28 NaN Y NaN Y \n", "29 NaN Y NaN Y \n", "30 NaN NaN NaN NaN " ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index(['Mailbox', 'Notes ID', 'Team Leader', 'Github account', 'Session 1',\n", " 'Unnamed: 5', 'Session 2', 'Unnamed: 7', 'Session 3', 'Unnamed: 9',\n", " 'Session 4', 'Unnamed: 11', 'Session 5', 'Unnamed: 13', 'Session 6',\n", " 'Unnamed: 15', 'Session 7', 'Unnamed: 17', 'Session 8'],\n", " dtype='object')" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.columns" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Session 1Session 2Session 3Session 4Session 5Session 6Session 7Session 8
Mailbox
pdlzhang@cn.ibm.comYYYYYNYY
yananzh@cn.ibm.comYYYYYN 项目会议冲突YY
lizhjdl@cn.ibm.comYN shiftN shiftN shiftN shiftN shiftN shiftN shift
yuanlyy@cn.ibm.comYYYN 项目会议冲突YYNY
shuyang@cn.ibm.comYYYYYYYN会议冲突
zhouyldl@cn.ibm.comYYYN 项目会议冲突YYYY
lizidl@cn.ibm.comYYYYYYYY
wangyih@cn.ibm.comYYYYYYYY
guoqq@cn.ibm.comYYYYYYYY
shangx@cn.ibm.comYYYYYYYY
xinzhdl@cn.ibm.comYYYYYYYY
ymying@cn.ibm.comYYYYYYYY
jmhjiang@cn.ibm.com迟到迟到YYYYYY
xiaoywdl@cn.ibm.comYYYYYN有其他会议YY
wpeter@cn.ibm.comYYNN跟客户有会NN跟客户有会YN
issczli@cn.ibm.comYYNNYYYY
zoujin@cn.ibm.comYYYN 项目会议冲突YYYN会议冲突
fygao@cn.ibm.comYN 项目会议冲突YYYYYY
dllsyliu@cn.ibm.comYYYYYYYY
dlwjia@cn.ibm.comYYYYYYYY
ssliu@cn.ibm.com早退YYN见客户YN跟客户有会议YN跟客户有会议
fenghao@cn.ibm.comNA(从第六节课来的插班生)NaNNaNNaNNaNYYY
xhongdl@cn.ibm.comYYYYYYYY
haojiedl@cn.ibm.comYYNYYYYY
mumeilun@cn.ibm.comYYNYYYYY
jinglil@cn.ibm.comYYYYYYYY
caijm@cn.ibm.comYYYYYYYY
lidannie@cn.ibm.comYYYYYYYY
dongmhtu@cn.ibm.comYYYYYYYY
zhangwyi@cn.ibm.comYYYYYYYY
zhanglp@cn.ibm.comNaNNaNNaNNaNNaNNaNNaN
\n", "
" ], "text/plain": [ " Session 1 Session 2 Session 3 Session 4 Session 5 \\\n", "Mailbox \n", "pdlzhang@cn.ibm.com Y Y Y Y Y \n", "yananzh@cn.ibm.com Y Y Y Y Y \n", "lizhjdl@cn.ibm.com Y N shift N shift N shift N shift \n", "yuanlyy@cn.ibm.com Y Y Y N 项目会议冲突 Y \n", "shuyang@cn.ibm.com Y Y Y Y Y \n", "zhouyldl@cn.ibm.com Y Y Y N 项目会议冲突 Y \n", "lizidl@cn.ibm.com Y Y Y Y Y \n", "wangyih@cn.ibm.com Y Y Y Y Y \n", "guoqq@cn.ibm.com Y Y Y Y Y \n", "shangx@cn.ibm.com Y Y Y Y Y \n", "xinzhdl@cn.ibm.com Y Y Y Y Y \n", "ymying@cn.ibm.com Y Y Y Y Y \n", "jmhjiang@cn.ibm.com 迟到 迟到 Y Y Y \n", "xiaoywdl@cn.ibm.com Y Y Y Y Y \n", "wpeter@cn.ibm.com Y Y N N跟客户有会 N \n", "issczli@cn.ibm.com Y Y N N Y \n", "zoujin@cn.ibm.com Y Y Y N 项目会议冲突 Y \n", "fygao@cn.ibm.com Y N 项目会议冲突 Y Y Y \n", "dllsyliu@cn.ibm.com Y Y Y Y Y \n", "dlwjia@cn.ibm.com Y Y Y Y Y \n", "ssliu@cn.ibm.com 早退 Y Y N见客户 Y \n", "fenghao@cn.ibm.com NA(从第六节课来的插班生) NaN NaN NaN NaN \n", "xhongdl@cn.ibm.com Y Y Y Y Y \n", "haojiedl@cn.ibm.com Y Y N Y Y \n", "mumeilun@cn.ibm.com Y Y N Y Y \n", "jinglil@cn.ibm.com Y Y Y Y Y \n", "caijm@cn.ibm.com Y Y Y Y Y \n", "lidannie@cn.ibm.com Y Y Y Y Y \n", "dongmhtu@cn.ibm.com Y Y Y Y Y \n", "zhangwyi@cn.ibm.com Y Y Y Y Y \n", "zhanglp@cn.ibm.com NaN NaN NaN NaN \n", "\n", " Session 6 Session 7 Session 8 \n", "Mailbox \n", "pdlzhang@cn.ibm.com N Y Y \n", "yananzh@cn.ibm.com N 项目会议冲突 Y Y \n", "lizhjdl@cn.ibm.com N shift N shift N shift \n", "yuanlyy@cn.ibm.com Y N Y \n", "shuyang@cn.ibm.com Y Y N会议冲突 \n", "zhouyldl@cn.ibm.com Y Y Y \n", "lizidl@cn.ibm.com Y Y Y \n", "wangyih@cn.ibm.com Y Y Y \n", "guoqq@cn.ibm.com Y Y Y \n", "shangx@cn.ibm.com Y Y Y \n", "xinzhdl@cn.ibm.com Y Y Y \n", "ymying@cn.ibm.com Y Y Y \n", "jmhjiang@cn.ibm.com Y Y Y \n", "xiaoywdl@cn.ibm.com N有其他会议 Y Y \n", "wpeter@cn.ibm.com N跟客户有会 Y N \n", "issczli@cn.ibm.com Y Y Y \n", "zoujin@cn.ibm.com Y Y N会议冲突 \n", "fygao@cn.ibm.com Y Y Y \n", "dllsyliu@cn.ibm.com Y Y Y \n", "dlwjia@cn.ibm.com Y Y Y \n", "ssliu@cn.ibm.com N跟客户有会议 Y N跟客户有会议 \n", "fenghao@cn.ibm.com Y Y Y \n", "xhongdl@cn.ibm.com Y Y Y \n", "haojiedl@cn.ibm.com Y Y Y \n", "mumeilun@cn.ibm.com Y Y Y \n", "jinglil@cn.ibm.com Y Y Y \n", "caijm@cn.ibm.com Y Y Y \n", "lidannie@cn.ibm.com Y Y Y \n", "dongmhtu@cn.ibm.com Y Y Y \n", "zhangwyi@cn.ibm.com Y Y Y \n", "zhanglp@cn.ibm.com NaN NaN NaN " ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_attend = df[[ f'Session {x}' for x in range(1, 9)]].set_index(df['Mailbox'])\n", "df_attend" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "def countY(row):\n", " return row[row =='Y'].size" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Mailbox\n", "pdlzhang@cn.ibm.com 7\n", "yananzh@cn.ibm.com 7\n", "lizhjdl@cn.ibm.com 1\n", "yuanlyy@cn.ibm.com 6\n", "shuyang@cn.ibm.com 7\n", "zhouyldl@cn.ibm.com 7\n", "lizidl@cn.ibm.com 8\n", "wangyih@cn.ibm.com 8\n", "guoqq@cn.ibm.com 8\n", "shangx@cn.ibm.com 8\n", "xinzhdl@cn.ibm.com 8\n", "ymying@cn.ibm.com 8\n", "jmhjiang@cn.ibm.com 6\n", "xiaoywdl@cn.ibm.com 7\n", "wpeter@cn.ibm.com 3\n", "issczli@cn.ibm.com 6\n", "zoujin@cn.ibm.com 6\n", "fygao@cn.ibm.com 5\n", "dllsyliu@cn.ibm.com 8\n", "dlwjia@cn.ibm.com 8\n", "ssliu@cn.ibm.com 4\n", "fenghao@cn.ibm.com 3\n", "xhongdl@cn.ibm.com 8\n", "haojiedl@cn.ibm.com 7\n", "mumeilun@cn.ibm.com 7\n", "jinglil@cn.ibm.com 8\n", "caijm@cn.ibm.com 8\n", "lidannie@cn.ibm.com 8\n", "dongmhtu@cn.ibm.com 8\n", "zhangwyi@cn.ibm.com 8\n", "zhanglp@cn.ibm.com 0\n", "dtype: int64" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_attend_count = df_attend.apply(countY, axis=1)\n", "df_attend_count" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "df_attend_count = pd.DataFrame(df_attend_count)" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "df_attend_count.columns = ['count']" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "df_attend_count['name'] = df_attend_count.index" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Mailboxcountname
0pdlzhang@cn.ibm.com7pdlzhang@cn.ibm.com
1yananzh@cn.ibm.com7yananzh@cn.ibm.com
2lizhjdl@cn.ibm.com1lizhjdl@cn.ibm.com
3yuanlyy@cn.ibm.com6yuanlyy@cn.ibm.com
4shuyang@cn.ibm.com7shuyang@cn.ibm.com
5zhouyldl@cn.ibm.com7zhouyldl@cn.ibm.com
6lizidl@cn.ibm.com8lizidl@cn.ibm.com
7wangyih@cn.ibm.com8wangyih@cn.ibm.com
8guoqq@cn.ibm.com8guoqq@cn.ibm.com
9shangx@cn.ibm.com8shangx@cn.ibm.com
10xinzhdl@cn.ibm.com8xinzhdl@cn.ibm.com
11ymying@cn.ibm.com8ymying@cn.ibm.com
12jmhjiang@cn.ibm.com6jmhjiang@cn.ibm.com
13xiaoywdl@cn.ibm.com7xiaoywdl@cn.ibm.com
14wpeter@cn.ibm.com3wpeter@cn.ibm.com
15issczli@cn.ibm.com6issczli@cn.ibm.com
16zoujin@cn.ibm.com6zoujin@cn.ibm.com
17fygao@cn.ibm.com5fygao@cn.ibm.com
18dllsyliu@cn.ibm.com8dllsyliu@cn.ibm.com
19dlwjia@cn.ibm.com8dlwjia@cn.ibm.com
20ssliu@cn.ibm.com4ssliu@cn.ibm.com
21fenghao@cn.ibm.com3fenghao@cn.ibm.com
22xhongdl@cn.ibm.com8xhongdl@cn.ibm.com
23haojiedl@cn.ibm.com7haojiedl@cn.ibm.com
24mumeilun@cn.ibm.com7mumeilun@cn.ibm.com
25jinglil@cn.ibm.com8jinglil@cn.ibm.com
26caijm@cn.ibm.com8caijm@cn.ibm.com
27lidannie@cn.ibm.com8lidannie@cn.ibm.com
28dongmhtu@cn.ibm.com8dongmhtu@cn.ibm.com
29zhangwyi@cn.ibm.com8zhangwyi@cn.ibm.com
30zhanglp@cn.ibm.com0zhanglp@cn.ibm.com
\n", "
" ], "text/plain": [ " Mailbox count name\n", "0 pdlzhang@cn.ibm.com 7 pdlzhang@cn.ibm.com\n", "1 yananzh@cn.ibm.com 7 yananzh@cn.ibm.com\n", "2 lizhjdl@cn.ibm.com 1 lizhjdl@cn.ibm.com\n", "3 yuanlyy@cn.ibm.com 6 yuanlyy@cn.ibm.com\n", "4 shuyang@cn.ibm.com 7 shuyang@cn.ibm.com\n", "5 zhouyldl@cn.ibm.com 7 zhouyldl@cn.ibm.com\n", "6 lizidl@cn.ibm.com 8 lizidl@cn.ibm.com\n", "7 wangyih@cn.ibm.com 8 wangyih@cn.ibm.com\n", "8 guoqq@cn.ibm.com 8 guoqq@cn.ibm.com\n", "9 shangx@cn.ibm.com 8 shangx@cn.ibm.com\n", "10 xinzhdl@cn.ibm.com 8 xinzhdl@cn.ibm.com\n", "11 ymying@cn.ibm.com 8 ymying@cn.ibm.com\n", "12 jmhjiang@cn.ibm.com 6 jmhjiang@cn.ibm.com\n", "13 xiaoywdl@cn.ibm.com 7 xiaoywdl@cn.ibm.com\n", "14 wpeter@cn.ibm.com 3 wpeter@cn.ibm.com\n", "15 issczli@cn.ibm.com 6 issczli@cn.ibm.com\n", "16 zoujin@cn.ibm.com 6 zoujin@cn.ibm.com\n", "17 fygao@cn.ibm.com 5 fygao@cn.ibm.com\n", "18 dllsyliu@cn.ibm.com 8 dllsyliu@cn.ibm.com\n", "19 dlwjia@cn.ibm.com 8 dlwjia@cn.ibm.com\n", "20 ssliu@cn.ibm.com 4 ssliu@cn.ibm.com\n", "21 fenghao@cn.ibm.com 3 fenghao@cn.ibm.com\n", "22 xhongdl@cn.ibm.com 8 xhongdl@cn.ibm.com\n", "23 haojiedl@cn.ibm.com 7 haojiedl@cn.ibm.com\n", "24 mumeilun@cn.ibm.com 7 mumeilun@cn.ibm.com\n", "25 jinglil@cn.ibm.com 8 jinglil@cn.ibm.com\n", "26 caijm@cn.ibm.com 8 caijm@cn.ibm.com\n", "27 lidannie@cn.ibm.com 8 lidannie@cn.ibm.com\n", "28 dongmhtu@cn.ibm.com 8 dongmhtu@cn.ibm.com\n", "29 zhangwyi@cn.ibm.com 8 zhangwyi@cn.ibm.com\n", "30 zhanglp@cn.ibm.com 0 zhanglp@cn.ibm.com" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_attend_count.reset_index(inplace=True)\n", "df_attend_count" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "df_attend_count['Mailbox'] = df_attend_count['Mailbox'].apply(lambda x: x[:x.find('@')])" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Mailboxcountname
0pdlzhang7pdlzhang@cn.ibm.com
1yananzh7yananzh@cn.ibm.com
2lizhjdl1lizhjdl@cn.ibm.com
3yuanlyy6yuanlyy@cn.ibm.com
4shuyang7shuyang@cn.ibm.com
5zhouyldl7zhouyldl@cn.ibm.com
6lizidl8lizidl@cn.ibm.com
7wangyih8wangyih@cn.ibm.com
8guoqq8guoqq@cn.ibm.com
9shangx8shangx@cn.ibm.com
10xinzhdl8xinzhdl@cn.ibm.com
11ymying8ymying@cn.ibm.com
12jmhjiang6jmhjiang@cn.ibm.com
13xiaoywdl7xiaoywdl@cn.ibm.com
14wpeter3wpeter@cn.ibm.com
15issczli6issczli@cn.ibm.com
16zoujin6zoujin@cn.ibm.com
17fygao5fygao@cn.ibm.com
18dllsyliu8dllsyliu@cn.ibm.com
19dlwjia8dlwjia@cn.ibm.com
20ssliu4ssliu@cn.ibm.com
21fenghao3fenghao@cn.ibm.com
22xhongdl8xhongdl@cn.ibm.com
23haojiedl7haojiedl@cn.ibm.com
24mumeilun7mumeilun@cn.ibm.com
25jinglil8jinglil@cn.ibm.com
26caijm8caijm@cn.ibm.com
27lidannie8lidannie@cn.ibm.com
28dongmhtu8dongmhtu@cn.ibm.com
29zhangwyi8zhangwyi@cn.ibm.com
30zhanglp0zhanglp@cn.ibm.com
\n", "
" ], "text/plain": [ " Mailbox count name\n", "0 pdlzhang 7 pdlzhang@cn.ibm.com\n", "1 yananzh 7 yananzh@cn.ibm.com\n", "2 lizhjdl 1 lizhjdl@cn.ibm.com\n", "3 yuanlyy 6 yuanlyy@cn.ibm.com\n", "4 shuyang 7 shuyang@cn.ibm.com\n", "5 zhouyldl 7 zhouyldl@cn.ibm.com\n", "6 lizidl 8 lizidl@cn.ibm.com\n", "7 wangyih 8 wangyih@cn.ibm.com\n", "8 guoqq 8 guoqq@cn.ibm.com\n", "9 shangx 8 shangx@cn.ibm.com\n", "10 xinzhdl 8 xinzhdl@cn.ibm.com\n", "11 ymying 8 ymying@cn.ibm.com\n", "12 jmhjiang 6 jmhjiang@cn.ibm.com\n", "13 xiaoywdl 7 xiaoywdl@cn.ibm.com\n", "14 wpeter 3 wpeter@cn.ibm.com\n", "15 issczli 6 issczli@cn.ibm.com\n", "16 zoujin 6 zoujin@cn.ibm.com\n", "17 fygao 5 fygao@cn.ibm.com\n", "18 dllsyliu 8 dllsyliu@cn.ibm.com\n", "19 dlwjia 8 dlwjia@cn.ibm.com\n", "20 ssliu 4 ssliu@cn.ibm.com\n", "21 fenghao 3 fenghao@cn.ibm.com\n", "22 xhongdl 8 xhongdl@cn.ibm.com\n", "23 haojiedl 7 haojiedl@cn.ibm.com\n", "24 mumeilun 7 mumeilun@cn.ibm.com\n", "25 jinglil 8 jinglil@cn.ibm.com\n", "26 caijm 8 caijm@cn.ibm.com\n", "27 lidannie 8 lidannie@cn.ibm.com\n", "28 dongmhtu 8 dongmhtu@cn.ibm.com\n", "29 zhangwyi 8 zhangwyi@cn.ibm.com\n", "30 zhanglp 0 zhanglp@cn.ibm.com" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_attend_count" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(20,10))\n", "plt.title('attending')\n", "# plt.plot()\n", "plt.bar(df_attend_count['Mailbox'], df_attend_count['count'])\n", "plt.xticks(rotation=70)\n", "plt.xlabel('name')\n", "plt.ylabel('count')\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.3" } }, "nbformat": 4, "nbformat_minor": 2 }