Commit @87f9c4bf4b9f69e7b73175442b97226526d14265

안효원 2022-05-23

dayend

@87f9c4bf4b9f69e7b73175442b97226526d14265

2fd99cb

20220523/.ipynb_checkpoints/Untitled-checkpoint.ipynb (deleted)

--- 20220523/.ipynb_checkpoints/Untitled-checkpoint.ipynb

...	...	@@ -1,342 +0,0 @@
	1	-{
	2	- "cells": [
	3	- {
	4	- "cell_type": "code",
	5	- "execution_count": 3,
	6	- "id": "db15e6b0",
	7	- "metadata": {},
	8	- "outputs": [],
	9	- "source": [
	10	- "import pandas as pd\n",
	11	- "import numpy as np"
	12	- ]
	13	- },
	14	- {
	15	- "cell_type": "code",
	16	- "execution_count": 4,
	17	- "id": "b8c06531",
	18	- "metadata": {},
	19	- "outputs": [],
	20	- "source": [
	21	- "df1 = pd.DataFrame({\n",
	22	- " 'A':['A0', 'A1', 'A2', 'A3'], \n",
	23	- " 'B':['B0', 'B1', 'B2', 'B3'],\n",
	24	- " 'C':['C0', 'C1', 'C2', 'C3']\n",
	25	- "})"
	26	- ]
	27	- },
	28	- {
	29	- "cell_type": "code",
	30	- "execution_count": 5,
	31	- "id": "ddffffb2",
	32	- "metadata": {},
	33	- "outputs": [
	34	- {
	35	- "data": {
	36	- "text/html": [
	37	- "<div>\n",
	38	- "<style scoped>\n",
	39	- " .dataframe tbody tr th:only-of-type {\n",
	40	- " vertical-align: middle;\n",
	41	- " }\n",
	42	- "\n",
	43	- " .dataframe tbody tr th {\n",
	44	- " vertical-align: top;\n",
	45	- " }\n",
	46	- "\n",
	47	- " .dataframe thead th {\n",
	48	- " text-align: right;\n",
	49	- " }\n",
	50	- "</style>\n",
	51	- "<table border=\"1\" class=\"dataframe\">\n",
	52	- " <thead>\n",
	53	- " <tr style=\"text-align: right;\">\n",
	54	- " <th></th>\n",
	55	- " <th>A</th>\n",
	56	- " <th>B</th>\n",
	57	- " <th>C</th>\n",
	58	- " </tr>\n",
	59	- " </thead>\n",
	60	- " <tbody>\n",
	61	- " <tr>\n",
	62	- " <th>0</th>\n",
	63	- " <td>A0</td>\n",
	64	- " <td>B0</td>\n",
	65	- " <td>C0</td>\n",
	66	- " </tr>\n",
	67	- " <tr>\n",
	68	- " <th>1</th>\n",
	69	- " <td>A1</td>\n",
	70	- " <td>B1</td>\n",
	71	- " <td>C1</td>\n",
	72	- " </tr>\n",
	73	- " <tr>\n",
	74	- " <th>2</th>\n",
	75	- " <td>A2</td>\n",
	76	- " <td>B2</td>\n",
	77	- " <td>C2</td>\n",
	78	- " </tr>\n",
	79	- " <tr>\n",
	80	- " <th>3</th>\n",
	81	- " <td>A3</td>\n",
	82	- " <td>B3</td>\n",
	83	- " <td>C3</td>\n",
	84	- " </tr>\n",
	85	- " </tbody>\n",
	86	- "</table>\n",
	87	- "</div>"
	88	- ],
	89	- "text/plain": [
	90	- " A B C\n",
	91	- "0 A0 B0 C0\n",
	92	- "1 A1 B1 C1\n",
	93	- "2 A2 B2 C2\n",
	94	- "3 A3 B3 C3"
	95	- ]
	96	- },
	97	- "execution_count": 5,
	98	- "metadata": {},
	99	- "output_type": "execute_result"
	100	- }
	101	- ],
	102	- "source": [
	103	- "df1"
	104	- ]
	105	- },
	106	- {
	107	- "cell_type": "code",
	108	- "execution_count": 8,
	109	- "id": "77e48c08",
	110	- "metadata": {},
	111	- "outputs": [],
	112	- "source": [
	113	- "df2 = pd.DataFrame({\n",
	114	- " 'A':['A4', 'A5', 'A6', 'A7'], \n",
	115	- " 'B':['B4', 'B5', 'B6', 'B7'],\n",
	116	- " 'C':['C4', 'C5', 'C6', 'C7']},index=(4, 5, 6, 7))"
	117	- ]
	118	- },
	119	- {
	120	- "cell_type": "code",
	121	- "execution_count": 9,
	122	- "id": "003f2363",
	123	- "metadata": {},
	124	- "outputs": [
	125	- {
	126	- "data": {
	127	- "text/html": [
	128	- "<div>\n",
	129	- "<style scoped>\n",
	130	- " .dataframe tbody tr th:only-of-type {\n",
	131	- " vertical-align: middle;\n",
	132	- " }\n",
	133	- "\n",
	134	- " .dataframe tbody tr th {\n",
	135	- " vertical-align: top;\n",
	136	- " }\n",
	137	- "\n",
	138	- " .dataframe thead th {\n",
	139	- " text-align: right;\n",
	140	- " }\n",
	141	- "</style>\n",
	142	- "<table border=\"1\" class=\"dataframe\">\n",
	143	- " <thead>\n",
	144	- " <tr style=\"text-align: right;\">\n",
	145	- " <th></th>\n",
	146	- " <th>A</th>\n",
	147	- " <th>B</th>\n",
	148	- " <th>C</th>\n",
	149	- " </tr>\n",
	150	- " </thead>\n",
	151	- " <tbody>\n",
	152	- " <tr>\n",
	153	- " <th>4</th>\n",
	154	- " <td>A4</td>\n",
	155	- " <td>B4</td>\n",
	156	- " <td>C4</td>\n",
	157	- " </tr>\n",
	158	- " <tr>\n",
	159	- " <th>5</th>\n",
	160	- " <td>A5</td>\n",
	161	- " <td>B5</td>\n",
	162	- " <td>C5</td>\n",
	163	- " </tr>\n",
	164	- " <tr>\n",
	165	- " <th>6</th>\n",
	166	- " <td>A6</td>\n",
	167	- " <td>B6</td>\n",
	168	- " <td>C6</td>\n",
	169	- " </tr>\n",
	170	- " <tr>\n",
	171	- " <th>7</th>\n",
	172	- " <td>A7</td>\n",
	173	- " <td>B7</td>\n",
	174	- " <td>C7</td>\n",
	175	- " </tr>\n",
	176	- " </tbody>\n",
	177	- "</table>\n",
	178	- "</div>"
	179	- ],
	180	- "text/plain": [
	181	- " A B C\n",
	182	- "4 A4 B4 C4\n",
	183	- "5 A5 B5 C5\n",
	184	- "6 A6 B6 C6\n",
	185	- "7 A7 B7 C7"
	186	- ]
	187	- },
	188	- "execution_count": 9,
	189	- "metadata": {},
	190	- "output_type": "execute_result"
	191	- }
	192	- ],
	193	- "source": [
	194	- "df2"
	195	- ]
	196	- },
	197	- {
	198	- "cell_type": "code",
	199	- "execution_count": 11,
	200	- "id": "67b45e7f",
	201	- "metadata": {},
	202	- "outputs": [],
	203	- "source": [
	204	- "df3 = pd.DataFrame({\n",
	205	- " 'A':['A8', 'A9', 'A10', 'A11'],\n",
	206	- " 'B':['B8', 'B9', 'B10', 'B11'],\n",
	207	- " 'C':['C8', 'C9', 'C10', 'C11']}, index=(8, 9, 10, 11))"
	208	- ]
	209	- },
	210	- {
	211	- "cell_type": "code",
	212	- "execution_count": 12,
	213	- "id": "5b9fa540",
	214	- "metadata": {},
	215	- "outputs": [
	216	- {
	217	- "data": {
	218	- "text/html": [
	219	- "<div>\n",
	220	- "<style scoped>\n",
	221	- " .dataframe tbody tr th:only-of-type {\n",
	222	- " vertical-align: middle;\n",
	223	- " }\n",
	224	- "\n",
	225	- " .dataframe tbody tr th {\n",
	226	- " vertical-align: top;\n",
	227	- " }\n",
	228	- "\n",
	229	- " .dataframe thead th {\n",
	230	- " text-align: right;\n",
	231	- " }\n",
	232	- "</style>\n",
	233	- "<table border=\"1\" class=\"dataframe\">\n",
	234	- " <thead>\n",
	235	- " <tr style=\"text-align: right;\">\n",
	236	- " <th></th>\n",
	237	- " <th>A</th>\n",
	238	- " <th>B</th>\n",
	239	- " <th>C</th>\n",
	240	- " </tr>\n",
	241	- " </thead>\n",
	242	- " <tbody>\n",
	243	- " <tr>\n",
	244	- " <th>8</th>\n",
	245	- " <td>A8</td>\n",
	246	- " <td>B8</td>\n",
	247	- " <td>C8</td>\n",
	248	- " </tr>\n",
	249	- " <tr>\n",
	250	- " <th>9</th>\n",
	251	- " <td>A9</td>\n",
	252	- " <td>B9</td>\n",
	253	- " <td>C9</td>\n",
	254	- " </tr>\n",
	255	- " <tr>\n",
	256	- " <th>10</th>\n",
	257	- " <td>A10</td>\n",
	258	- " <td>B10</td>\n",
	259	- " <td>C10</td>\n",
	260	- " </tr>\n",
	261	- " <tr>\n",
	262	- " <th>11</th>\n",
	263	- " <td>A11</td>\n",
	264	- " <td>B11</td>\n",
	265	- " <td>C11</td>\n",
	266	- " </tr>\n",
	267	- " </tbody>\n",
	268	- "</table>\n",
	269	- "</div>"
	270	- ],
	271	- "text/plain": [
	272	- " A B C\n",
	273	- "8 A8 B8 C8\n",
	274	- "9 A9 B9 C9\n",
	275	- "10 A10 B10 C10\n",
	276	- "11 A11 B11 C11"
	277	- ]
	278	- },
	279	- "execution_count": 12,
	280	- "metadata": {},
	281	- "output_type": "execute_result"
	282	- }
	283	- ],
	284	- "source": [
	285	- "df3"
	286	- ]
	287	- },
	288	- {
	289	- "cell_type": "code",
	290	- "execution_count": null,
	291	- "id": "f41bb709",
	292	- "metadata": {},
	293	- "outputs": [],
	294	- "source": []
	295	- },
	296	- {
	297	- "cell_type": "code",
	298	- "execution_count": null,
	299	- "id": "7950586b",
	300	- "metadata": {},
	301	- "outputs": [],
	302	- "source": []
	303	- },
	304	- {
	305	- "cell_type": "code",
	306	- "execution_count": null,
	307	- "id": "35a3b4ba",
	308	- "metadata": {},
	309	- "outputs": [],
	310	- "source": []
	311	- },
	312	- {
	313	- "cell_type": "code",
	314	- "execution_count": null,
	315	- "id": "5424e7b4",
	316	- "metadata": {},
	317	- "outputs": [],
	318	- "source": []
	319	- }
	320	- ],
	321	- "metadata": {
	322	- "kernelspec": {
	323	- "display_name": "Python 3 (ipykernel)",
	324	- "language": "python",
	325	- "name": "python3"
	326	- },
	327	- "language_info": {
	328	- "codemirror_mode": {
	329	- "name": "ipython",
	330	- "version": 3
	331	- },
	332	- "file_extension": ".py",
	333	- "mimetype": "text/x-python",
	334	- "name": "python",
	335	- "nbconvert_exporter": "python",
	336	- "pygments_lexer": "ipython3",
	337	- "version": "3.9.7"
	338	- }
	339	- },
	340	- "nbformat": 4,
	341	- "nbformat_minor": 5
	342	-}

87f9c4b

20220523/.ipynb_checkpoints/dataframe-checkpoint.ipynb (added)

+++ 20220523/.ipynb_checkpoints/dataframe-checkpoint.ipynb

...	...	@@ -0,0 +1,1975 @@
	1	+{
	2	+ "cells": [
	3	+ {
	4	+ "cell_type": "code",
	5	+ "execution_count": 3,
	6	+ "id": "5146a34e",
	7	+ "metadata": {},
	8	+ "outputs": [],
	9	+ "source": [
	10	+ "import pandas as pd\n",
	11	+ "import numpy as np"
	12	+ ]
	13	+ },
	14	+ {
	15	+ "cell_type": "code",
	16	+ "execution_count": 13,
	17	+ "id": "a8c55879",
	18	+ "metadata": {},
	19	+ "outputs": [],
	20	+ "source": [
	21	+ "df1 = pd.DataFrame({\n",
	22	+ " 'A':['A0', 'A1', 'A2', 'A3'], \n",
	23	+ " 'B':['B0', 'B1', 'B2', 'B3'],\n",
	24	+ " 'C':['C0', 'C1', 'C2', 'C3']\n",
	25	+ "})"
	26	+ ]
	27	+ },
	28	+ {
	29	+ "cell_type": "code",
	30	+ "execution_count": 14,
	31	+ "id": "22aa890a",
	32	+ "metadata": {},
	33	+ "outputs": [
	34	+ {
	35	+ "data": {
	36	+ "text/html": [
	37	+ "<div>\n",
	38	+ "<style scoped>\n",
	39	+ " .dataframe tbody tr th:only-of-type {\n",
	40	+ " vertical-align: middle;\n",
	41	+ " }\n",
	42	+ "\n",
	43	+ " .dataframe tbody tr th {\n",
	44	+ " vertical-align: top;\n",
	45	+ " }\n",
	46	+ "\n",
	47	+ " .dataframe thead th {\n",
	48	+ " text-align: right;\n",
	49	+ " }\n",
	50	+ "</style>\n",
	51	+ "<table border=\"1\" class=\"dataframe\">\n",
	52	+ " <thead>\n",
	53	+ " <tr style=\"text-align: right;\">\n",
	54	+ " <th></th>\n",
	55	+ " <th>A</th>\n",
	56	+ " <th>B</th>\n",
	57	+ " <th>C</th>\n",
	58	+ " </tr>\n",
	59	+ " </thead>\n",
	60	+ " <tbody>\n",
	61	+ " <tr>\n",
	62	+ " <th>0</th>\n",
	63	+ " <td>A0</td>\n",
	64	+ " <td>B0</td>\n",
	65	+ " <td>C0</td>\n",
	66	+ " </tr>\n",
	67	+ " <tr>\n",
	68	+ " <th>1</th>\n",
	69	+ " <td>A1</td>\n",
	70	+ " <td>B1</td>\n",
	71	+ " <td>C1</td>\n",
	72	+ " </tr>\n",
	73	+ " <tr>\n",
	74	+ " <th>2</th>\n",
	75	+ " <td>A2</td>\n",
	76	+ " <td>B2</td>\n",
	77	+ " <td>C2</td>\n",
	78	+ " </tr>\n",
	79	+ " <tr>\n",
	80	+ " <th>3</th>\n",
	81	+ " <td>A3</td>\n",
	82	+ " <td>B3</td>\n",
	83	+ " <td>C3</td>\n",
	84	+ " </tr>\n",
	85	+ " </tbody>\n",
	86	+ "</table>\n",
	87	+ "</div>"
	88	+ ],
	89	+ "text/plain": [
	90	+ " A B C\n",
	91	+ "0 A0 B0 C0\n",
	92	+ "1 A1 B1 C1\n",
	93	+ "2 A2 B2 C2\n",
	94	+ "3 A3 B3 C3"
	95	+ ]
	96	+ },
	97	+ "execution_count": 14,
	98	+ "metadata": {},
	99	+ "output_type": "execute_result"
	100	+ }
	101	+ ],
	102	+ "source": [
	103	+ "df1"
	104	+ ]
	105	+ },
	106	+ {
	107	+ "cell_type": "code",
	108	+ "execution_count": 15,
	109	+ "id": "6c0701ab",
	110	+ "metadata": {},
	111	+ "outputs": [],
	112	+ "source": [
	113	+ "df2 = pd.DataFrame({\n",
	114	+ " 'A':['A4', 'A5', 'A6', 'A7'], \n",
	115	+ " 'B':['B4', 'B5', 'B6', 'B7'],\n",
	116	+ " 'C':['C4', 'C5', 'C6', 'C7']},index=(4, 5, 6, 7))"
	117	+ ]
	118	+ },
	119	+ {
	120	+ "cell_type": "code",
	121	+ "execution_count": 16,
	122	+ "id": "85ed1f0f",
	123	+ "metadata": {},
	124	+ "outputs": [
	125	+ {
	126	+ "data": {
	127	+ "text/html": [
	128	+ "<div>\n",
	129	+ "<style scoped>\n",
	130	+ " .dataframe tbody tr th:only-of-type {\n",
	131	+ " vertical-align: middle;\n",
	132	+ " }\n",
	133	+ "\n",
	134	+ " .dataframe tbody tr th {\n",
	135	+ " vertical-align: top;\n",
	136	+ " }\n",
	137	+ "\n",
	138	+ " .dataframe thead th {\n",
	139	+ " text-align: right;\n",
	140	+ " }\n",
	141	+ "</style>\n",
	142	+ "<table border=\"1\" class=\"dataframe\">\n",
	143	+ " <thead>\n",
	144	+ " <tr style=\"text-align: right;\">\n",
	145	+ " <th></th>\n",
	146	+ " <th>A</th>\n",
	147	+ " <th>B</th>\n",
	148	+ " <th>C</th>\n",
	149	+ " </tr>\n",
	150	+ " </thead>\n",
	151	+ " <tbody>\n",
	152	+ " <tr>\n",
	153	+ " <th>4</th>\n",
	154	+ " <td>A4</td>\n",
	155	+ " <td>B4</td>\n",
	156	+ " <td>C4</td>\n",
	157	+ " </tr>\n",
	158	+ " <tr>\n",
	159	+ " <th>5</th>\n",
	160	+ " <td>A5</td>\n",
	161	+ " <td>B5</td>\n",
	162	+ " <td>C5</td>\n",
	163	+ " </tr>\n",
	164	+ " <tr>\n",
	165	+ " <th>6</th>\n",
	166	+ " <td>A6</td>\n",
	167	+ " <td>B6</td>\n",
	168	+ " <td>C6</td>\n",
	169	+ " </tr>\n",
	170	+ " <tr>\n",
	171	+ " <th>7</th>\n",
	172	+ " <td>A7</td>\n",
	173	+ " <td>B7</td>\n",
	174	+ " <td>C7</td>\n",
	175	+ " </tr>\n",
	176	+ " </tbody>\n",
	177	+ "</table>\n",
	178	+ "</div>"
	179	+ ],
	180	+ "text/plain": [
	181	+ " A B C\n",
	182	+ "4 A4 B4 C4\n",
	183	+ "5 A5 B5 C5\n",
	184	+ "6 A6 B6 C6\n",
	185	+ "7 A7 B7 C7"
	186	+ ]
	187	+ },
	188	+ "execution_count": 16,
	189	+ "metadata": {},
	190	+ "output_type": "execute_result"
	191	+ }
	192	+ ],
	193	+ "source": [
	194	+ "df2"
	195	+ ]
	196	+ },
	197	+ {
	198	+ "cell_type": "code",
	199	+ "execution_count": 17,
	200	+ "id": "8a998f5a",
	201	+ "metadata": {},
	202	+ "outputs": [],
	203	+ "source": [
	204	+ "df3 = pd.DataFrame({\n",
	205	+ " 'A':['A8', 'A9', 'A10', 'A11'],\n",
	206	+ " 'B':['B8', 'B9', 'B10', 'B11'],\n",
	207	+ " 'C':['C8', 'C9', 'C10', 'C11']}, index=(8, 9, 10, 11))"
	208	+ ]
	209	+ },
	210	+ {
	211	+ "cell_type": "code",
	212	+ "execution_count": 18,
	213	+ "id": "70f74dd5",
	214	+ "metadata": {},
	215	+ "outputs": [
	216	+ {
	217	+ "data": {
	218	+ "text/html": [
	219	+ "<div>\n",
	220	+ "<style scoped>\n",
	221	+ " .dataframe tbody tr th:only-of-type {\n",
	222	+ " vertical-align: middle;\n",
	223	+ " }\n",
	224	+ "\n",
	225	+ " .dataframe tbody tr th {\n",
	226	+ " vertical-align: top;\n",
	227	+ " }\n",
	228	+ "\n",
	229	+ " .dataframe thead th {\n",
	230	+ " text-align: right;\n",
	231	+ " }\n",
	232	+ "</style>\n",
	233	+ "<table border=\"1\" class=\"dataframe\">\n",
	234	+ " <thead>\n",
	235	+ " <tr style=\"text-align: right;\">\n",
	236	+ " <th></th>\n",
	237	+ " <th>A</th>\n",
	238	+ " <th>B</th>\n",
	239	+ " <th>C</th>\n",
	240	+ " </tr>\n",
	241	+ " </thead>\n",
	242	+ " <tbody>\n",
	243	+ " <tr>\n",
	244	+ " <th>8</th>\n",
	245	+ " <td>A8</td>\n",
	246	+ " <td>B8</td>\n",
	247	+ " <td>C8</td>\n",
	248	+ " </tr>\n",
	249	+ " <tr>\n",
	250	+ " <th>9</th>\n",
	251	+ " <td>A9</td>\n",
	252	+ " <td>B9</td>\n",
	253	+ " <td>C9</td>\n",
	254	+ " </tr>\n",
	255	+ " <tr>\n",
	256	+ " <th>10</th>\n",
	257	+ " <td>A10</td>\n",
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	300	+ "execution_count": 22,
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	443	+ "Int64Index: 12 entries, 0 to 11\n",
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	462	+ "id": "b490ebea",
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	465	+ "source": [
	466	+ "result = pd.concat([df1, df2, df3], keys=['x', 'y', 'z'])"
	467	+ ]
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	471	+ "execution_count": 25,
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	749	+ "df4 = pd.DataFrame({\n",
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	751	+ " 'D':['D2', 'D3', 'D6', 'D7'],\n",
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	1232	+ " <th>6</th>\n",
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	1252	+ " A B C D F\n",
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	1263	+ "execution_count": 52,
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	1274	+ "execution_count": 56,
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	1300	+ " <th>B</th>\n",
	1301	+ " <th>C</th>\n",
	1302	+ " <th>B</th>\n",
	1303	+ " <th>D</th>\n",
	1304	+ " <th>F</th>\n",
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	1307	+ " <tbody>\n",
	1308	+ " <tr>\n",
	1309	+ " <th>2</th>\n",
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	1311	+ " <td>B2</td>\n",
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	1318	+ " <th>3</th>\n",
	1319	+ " <td>A3</td>\n",
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	1321	+ " <td>C3</td>\n",
	1322	+ " <td>B3</td>\n",
	1323	+ " <td>D3</td>\n",
	1324	+ " <td>F3</td>\n",
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	1331	+ " A B C B D F\n",
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	1333	+ "3 A3 B3 C3 B3 D3 F3"
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	1336	+ "execution_count": 56,
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	1347	+ "execution_count": 63,
	1348	+ "id": "241cc856",
	1349	+ "metadata": {},
	1350	+ "outputs": [],
	1351	+ "source": [
	1352	+ "left = pd.DataFrame({\n",
	1353	+ " 'key':['K0', 'K4', 'K2', 'K3'],\n",
	1354	+ " 'A':['A0', 'A1', 'A2', 'A3'],\n",
	1355	+ " 'B':['B0', 'B1', 'B2', 'B3']\n",
	1356	+ "})"
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	1360	+ "cell_type": "code",
	1361	+ "execution_count": 64,
	1362	+ "id": "7993c237",
	1363	+ "metadata": {},
	1364	+ "outputs": [],
	1365	+ "source": [
	1366	+ "right = pd.DataFrame({\n",
	1367	+ " 'key':['K', 'K1', 'K2', 'K3'],\n",
	1368	+ " 'C':['C0', 'C1', 'C2', 'C3'],\n",
	1369	+ " 'D':['D0', 'D1', 'D2', 'D3']\n",
	1370	+ "})"
	1371	+ ]
	1372	+ },
	1373	+ {
	1374	+ "cell_type": "code",
	1375	+ "execution_count": 65,
	1376	+ "id": "4ea20d17",
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	1397	+ " <thead>\n",
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	1399	+ " <th></th>\n",
	1400	+ " <th>key</th>\n",
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87f9c4b

20220523/.ipynb_checkpoints/pyplot-checkpoint.ipynb (added)

+++ 20220523/.ipynb_checkpoints/pyplot-checkpoint.ipynb

...	...	@@ -0,0 +1,6 @@
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	5	+ "nbformat_minor": 5
	6	+}

2fd99cb

20220523/Untitled.ipynb (deleted)

--- 20220523/Untitled.ipynb

...	...	@@ -1,342 +0,0 @@
	1	-{
	2	- "cells": [
	3	- {
	4	- "cell_type": "code",
	5	- "execution_count": 3,
	6	- "id": "db15e6b0",
	7	- "metadata": {},
	8	- "outputs": [],
	9	- "source": [
	10	- "import pandas as pd\n",
	11	- "import numpy as np"
	12	- ]
	13	- },
	14	- {
	15	- "cell_type": "code",
	16	- "execution_count": 4,
	17	- "id": "b8c06531",
	18	- "metadata": {},
	19	- "outputs": [],
	20	- "source": [
	21	- "df1 = pd.DataFrame({\n",
	22	- " 'A':['A0', 'A1', 'A2', 'A3'], \n",
	23	- " 'B':['B0', 'B1', 'B2', 'B3'],\n",
	24	- " 'C':['C0', 'C1', 'C2', 'C3']\n",
	25	- "})"
	26	- ]
	27	- },
	28	- {
	29	- "cell_type": "code",
	30	- "execution_count": 5,
	31	- "id": "ddffffb2",
	32	- "metadata": {},
	33	- "outputs": [
	34	- {
	35	- "data": {
	36	- "text/html": [
	37	- "<div>\n",
	38	- "<style scoped>\n",
	39	- " .dataframe tbody tr th:only-of-type {\n",
	40	- " vertical-align: middle;\n",
	41	- " }\n",
	42	- "\n",
	43	- " .dataframe tbody tr th {\n",
	44	- " vertical-align: top;\n",
	45	- " }\n",
	46	- "\n",
	47	- " .dataframe thead th {\n",
	48	- " text-align: right;\n",
	49	- " }\n",
	50	- "</style>\n",
	51	- "<table border=\"1\" class=\"dataframe\">\n",
	52	- " <thead>\n",
	53	- " <tr style=\"text-align: right;\">\n",
	54	- " <th></th>\n",
	55	- " <th>A</th>\n",
	56	- " <th>B</th>\n",
	57	- " <th>C</th>\n",
	58	- " </tr>\n",
	59	- " </thead>\n",
	60	- " <tbody>\n",
	61	- " <tr>\n",
	62	- " <th>0</th>\n",
	63	- " <td>A0</td>\n",
	64	- " <td>B0</td>\n",
	65	- " <td>C0</td>\n",
	66	- " </tr>\n",
	67	- " <tr>\n",
	68	- " <th>1</th>\n",
	69	- " <td>A1</td>\n",
	70	- " <td>B1</td>\n",
	71	- " <td>C1</td>\n",
	72	- " </tr>\n",
	73	- " <tr>\n",
	74	- " <th>2</th>\n",
	75	- " <td>A2</td>\n",
	76	- " <td>B2</td>\n",
	77	- " <td>C2</td>\n",
	78	- " </tr>\n",
	79	- " <tr>\n",
	80	- " <th>3</th>\n",
	81	- " <td>A3</td>\n",
	82	- " <td>B3</td>\n",
	83	- " <td>C3</td>\n",
	84	- " </tr>\n",
	85	- " </tbody>\n",
	86	- "</table>\n",
	87	- "</div>"
	88	- ],
	89	- "text/plain": [
	90	- " A B C\n",
	91	- "0 A0 B0 C0\n",
	92	- "1 A1 B1 C1\n",
	93	- "2 A2 B2 C2\n",
	94	- "3 A3 B3 C3"
	95	- ]
	96	- },
	97	- "execution_count": 5,
	98	- "metadata": {},
	99	- "output_type": "execute_result"
	100	- }
	101	- ],
	102	- "source": [
	103	- "df1"
	104	- ]
	105	- },
	106	- {
	107	- "cell_type": "code",
	108	- "execution_count": 8,
	109	- "id": "77e48c08",
	110	- "metadata": {},
	111	- "outputs": [],
	112	- "source": [
	113	- "df2 = pd.DataFrame({\n",
	114	- " 'A':['A4', 'A5', 'A6', 'A7'], \n",
	115	- " 'B':['B4', 'B5', 'B6', 'B7'],\n",
	116	- " 'C':['C4', 'C5', 'C6', 'C7']},index=(4, 5, 6, 7))"
	117	- ]
	118	- },
	119	- {
	120	- "cell_type": "code",
	121	- "execution_count": 9,
	122	- "id": "003f2363",
	123	- "metadata": {},
	124	- "outputs": [
	125	- {
	126	- "data": {
	127	- "text/html": [
	128	- "<div>\n",
	129	- "<style scoped>\n",
	130	- " .dataframe tbody tr th:only-of-type {\n",
	131	- " vertical-align: middle;\n",
	132	- " }\n",
	133	- "\n",
	134	- " .dataframe tbody tr th {\n",
	135	- " vertical-align: top;\n",
	136	- " }\n",
	137	- "\n",
	138	- " .dataframe thead th {\n",
	139	- " text-align: right;\n",
	140	- " }\n",
	141	- "</style>\n",
	142	- "<table border=\"1\" class=\"dataframe\">\n",
	143	- " <thead>\n",
	144	- " <tr style=\"text-align: right;\">\n",
	145	- " <th></th>\n",
	146	- " <th>A</th>\n",
	147	- " <th>B</th>\n",
	148	- " <th>C</th>\n",
	149	- " </tr>\n",
	150	- " </thead>\n",
	151	- " <tbody>\n",
	152	- " <tr>\n",
	153	- " <th>4</th>\n",
	154	- " <td>A4</td>\n",
	155	- " <td>B4</td>\n",
	156	- " <td>C4</td>\n",
	157	- " </tr>\n",
	158	- " <tr>\n",
	159	- " <th>5</th>\n",
	160	- " <td>A5</td>\n",
	161	- " <td>B5</td>\n",
	162	- " <td>C5</td>\n",
	163	- " </tr>\n",
	164	- " <tr>\n",
	165	- " <th>6</th>\n",
	166	- " <td>A6</td>\n",
	167	- " <td>B6</td>\n",
	168	- " <td>C6</td>\n",
	169	- " </tr>\n",
	170	- " <tr>\n",
	171	- " <th>7</th>\n",
	172	- " <td>A7</td>\n",
	173	- " <td>B7</td>\n",
	174	- " <td>C7</td>\n",
	175	- " </tr>\n",
	176	- " </tbody>\n",
	177	- "</table>\n",
	178	- "</div>"
	179	- ],
	180	- "text/plain": [
	181	- " A B C\n",
	182	- "4 A4 B4 C4\n",
	183	- "5 A5 B5 C5\n",
	184	- "6 A6 B6 C6\n",
	185	- "7 A7 B7 C7"
	186	- ]
	187	- },
	188	- "execution_count": 9,
	189	- "metadata": {},
	190	- "output_type": "execute_result"
	191	- }
	192	- ],
	193	- "source": [
	194	- "df2"
	195	- ]
	196	- },
	197	- {
	198	- "cell_type": "code",
	199	- "execution_count": 11,
	200	- "id": "67b45e7f",
	201	- "metadata": {},
	202	- "outputs": [],
	203	- "source": [
	204	- "df3 = pd.DataFrame({\n",
	205	- " 'A':['A8', 'A9', 'A10', 'A11'],\n",
	206	- " 'B':['B8', 'B9', 'B10', 'B11'],\n",
	207	- " 'C':['C8', 'C9', 'C10', 'C11']}, index=(8, 9, 10, 11))"
	208	- ]
	209	- },
	210	- {
	211	- "cell_type": "code",
	212	- "execution_count": 12,
	213	- "id": "5b9fa540",
	214	- "metadata": {},
	215	- "outputs": [
	216	- {
	217	- "data": {
	218	- "text/html": [
	219	- "<div>\n",
	220	- "<style scoped>\n",
	221	- " .dataframe tbody tr th:only-of-type {\n",
	222	- " vertical-align: middle;\n",
	223	- " }\n",
	224	- "\n",
	225	- " .dataframe tbody tr th {\n",
	226	- " vertical-align: top;\n",
	227	- " }\n",
	228	- "\n",
	229	- " .dataframe thead th {\n",
	230	- " text-align: right;\n",
	231	- " }\n",
	232	- "</style>\n",
	233	- "<table border=\"1\" class=\"dataframe\">\n",
	234	- " <thead>\n",
	235	- " <tr style=\"text-align: right;\">\n",
	236	- " <th></th>\n",
	237	- " <th>A</th>\n",
	238	- " <th>B</th>\n",
	239	- " <th>C</th>\n",
	240	- " </tr>\n",
	241	- " </thead>\n",
	242	- " <tbody>\n",
	243	- " <tr>\n",
	244	- " <th>8</th>\n",
	245	- " <td>A8</td>\n",
	246	- " <td>B8</td>\n",
	247	- " <td>C8</td>\n",
	248	- " </tr>\n",
	249	- " <tr>\n",
	250	- " <th>9</th>\n",
	251	- " <td>A9</td>\n",
	252	- " <td>B9</td>\n",
	253	- " <td>C9</td>\n",
	254	- " </tr>\n",
	255	- " <tr>\n",
	256	- " <th>10</th>\n",
	257	- " <td>A10</td>\n",
	258	- " <td>B10</td>\n",
	259	- " <td>C10</td>\n",
	260	- " </tr>\n",
	261	- " <tr>\n",
	262	- " <th>11</th>\n",
	263	- " <td>A11</td>\n",
	264	- " <td>B11</td>\n",
	265	- " <td>C11</td>\n",
	266	- " </tr>\n",
	267	- " </tbody>\n",
	268	- "</table>\n",
	269	- "</div>"
	270	- ],
	271	- "text/plain": [
	272	- " A B C\n",
	273	- "8 A8 B8 C8\n",
	274	- "9 A9 B9 C9\n",
	275	- "10 A10 B10 C10\n",
	276	- "11 A11 B11 C11"
	277	- ]
	278	- },
	279	- "execution_count": 12,
	280	- "metadata": {},
	281	- "output_type": "execute_result"
	282	- }
	283	- ],
	284	- "source": [
	285	- "df3"
	286	- ]
	287	- },
	288	- {
	289	- "cell_type": "code",
	290	- "execution_count": null,
	291	- "id": "f41bb709",
	292	- "metadata": {},
	293	- "outputs": [],
	294	- "source": []
	295	- },
	296	- {
	297	- "cell_type": "code",
	298	- "execution_count": null,
	299	- "id": "7950586b",
	300	- "metadata": {},
	301	- "outputs": [],
	302	- "source": []
	303	- },
	304	- {
	305	- "cell_type": "code",
	306	- "execution_count": null,
	307	- "id": "35a3b4ba",
	308	- "metadata": {},
	309	- "outputs": [],
	310	- "source": []
	311	- },
	312	- {
	313	- "cell_type": "code",
	314	- "execution_count": null,
	315	- "id": "5424e7b4",
	316	- "metadata": {},
	317	- "outputs": [],
	318	- "source": []
	319	- }
	320	- ],
	321	- "metadata": {
	322	- "kernelspec": {
	323	- "display_name": "Python 3 (ipykernel)",
	324	- "language": "python",
	325	- "name": "python3"
	326	- },
	327	- "language_info": {
	328	- "codemirror_mode": {
	329	- "name": "ipython",
	330	- "version": 3
	331	- },
	332	- "file_extension": ".py",
	333	- "mimetype": "text/x-python",
	334	- "name": "python",
	335	- "nbconvert_exporter": "python",
	336	- "pygments_lexer": "ipython3",
	337	- "version": "3.9.7"
	338	- }
	339	- },
	340	- "nbformat": 4,
	341	- "nbformat_minor": 5
	342	-}

87f9c4b

20220523/dataframe.ipynb (added)

+++ 20220523/dataframe.ipynb

...	...	@@ -0,0 +1,1975 @@
	1	+{
	2	+ "cells": [
	3	+ {
	4	+ "cell_type": "code",
	5	+ "execution_count": 3,
	6	+ "id": "5146a34e",
	7	+ "metadata": {},
	8	+ "outputs": [],
	9	+ "source": [
	10	+ "import pandas as pd\n",
	11	+ "import numpy as np"
	12	+ ]
	13	+ },
	14	+ {
	15	+ "cell_type": "code",
	16	+ "execution_count": 13,
	17	+ "id": "a8c55879",
	18	+ "metadata": {},
	19	+ "outputs": [],
	20	+ "source": [
	21	+ "df1 = pd.DataFrame({\n",
	22	+ " 'A':['A0', 'A1', 'A2', 'A3'], \n",
	23	+ " 'B':['B0', 'B1', 'B2', 'B3'],\n",
	24	+ " 'C':['C0', 'C1', 'C2', 'C3']\n",
	25	+ "})"
	26	+ ]
	27	+ },
	28	+ {
	29	+ "cell_type": "code",
	30	+ "execution_count": 14,
	31	+ "id": "22aa890a",
	32	+ "metadata": {},
	33	+ "outputs": [
	34	+ {
	35	+ "data": {
	36	+ "text/html": [
	37	+ "<div>\n",
	38	+ "<style scoped>\n",
	39	+ " .dataframe tbody tr th:only-of-type {\n",
	40	+ " vertical-align: middle;\n",
	41	+ " }\n",
	42	+ "\n",
	43	+ " .dataframe tbody tr th {\n",
	44	+ " vertical-align: top;\n",
	45	+ " }\n",
	46	+ "\n",
	47	+ " .dataframe thead th {\n",
	48	+ " text-align: right;\n",
	49	+ " }\n",
	50	+ "</style>\n",
	51	+ "<table border=\"1\" class=\"dataframe\">\n",
	52	+ " <thead>\n",
	53	+ " <tr style=\"text-align: right;\">\n",
	54	+ " <th></th>\n",
	55	+ " <th>A</th>\n",
	56	+ " <th>B</th>\n",
	57	+ " <th>C</th>\n",
	58	+ " </tr>\n",
	59	+ " </thead>\n",
	60	+ " <tbody>\n",
	61	+ " <tr>\n",
	62	+ " <th>0</th>\n",
	63	+ " <td>A0</td>\n",
	64	+ " <td>B0</td>\n",
	65	+ " <td>C0</td>\n",
	66	+ " </tr>\n",
	67	+ " <tr>\n",
	68	+ " <th>1</th>\n",
	69	+ " <td>A1</td>\n",
	70	+ " <td>B1</td>\n",
	71	+ " <td>C1</td>\n",
	72	+ " </tr>\n",
	73	+ " <tr>\n",
	74	+ " <th>2</th>\n",
	75	+ " <td>A2</td>\n",
	76	+ " <td>B2</td>\n",
	77	+ " <td>C2</td>\n",
	78	+ " </tr>\n",
	79	+ " <tr>\n",
	80	+ " <th>3</th>\n",
	81	+ " <td>A3</td>\n",
	82	+ " <td>B3</td>\n",
	83	+ " <td>C3</td>\n",
	84	+ " </tr>\n",
	85	+ " </tbody>\n",
	86	+ "</table>\n",
	87	+ "</div>"
	88	+ ],
	89	+ "text/plain": [
	90	+ " A B C\n",
	91	+ "0 A0 B0 C0\n",
	92	+ "1 A1 B1 C1\n",
	93	+ "2 A2 B2 C2\n",
	94	+ "3 A3 B3 C3"
	95	+ ]
	96	+ },
	97	+ "execution_count": 14,
	98	+ "metadata": {},
	99	+ "output_type": "execute_result"
	100	+ }
	101	+ ],
	102	+ "source": [
	103	+ "df1"
	104	+ ]
	105	+ },
	106	+ {
	107	+ "cell_type": "code",
	108	+ "execution_count": 15,
	109	+ "id": "6c0701ab",
	110	+ "metadata": {},
	111	+ "outputs": [],
	112	+ "source": [
	113	+ "df2 = pd.DataFrame({\n",
	114	+ " 'A':['A4', 'A5', 'A6', 'A7'], \n",
	115	+ " 'B':['B4', 'B5', 'B6', 'B7'],\n",
	116	+ " 'C':['C4', 'C5', 'C6', 'C7']},index=(4, 5, 6, 7))"
	117	+ ]
	118	+ },
	119	+ {
	120	+ "cell_type": "code",
	121	+ "execution_count": 16,
	122	+ "id": "85ed1f0f",
	123	+ "metadata": {},
	124	+ "outputs": [
	125	+ {
	126	+ "data": {
	127	+ "text/html": [
	128	+ "<div>\n",
	129	+ "<style scoped>\n",
	130	+ " .dataframe tbody tr th:only-of-type {\n",
	131	+ " vertical-align: middle;\n",
	132	+ " }\n",
	133	+ "\n",
	134	+ " .dataframe tbody tr th {\n",
	135	+ " vertical-align: top;\n",
	136	+ " }\n",
	137	+ "\n",
	138	+ " .dataframe thead th {\n",
	139	+ " text-align: right;\n",
	140	+ " }\n",
	141	+ "</style>\n",
	142	+ "<table border=\"1\" class=\"dataframe\">\n",
	143	+ " <thead>\n",
	144	+ " <tr style=\"text-align: right;\">\n",
	145	+ " <th></th>\n",
	146	+ " <th>A</th>\n",
	147	+ " <th>B</th>\n",
	148	+ " <th>C</th>\n",
	149	+ " </tr>\n",
	150	+ " </thead>\n",
	151	+ " <tbody>\n",
	152	+ " <tr>\n",
	153	+ " <th>4</th>\n",
	154	+ " <td>A4</td>\n",
	155	+ " <td>B4</td>\n",
	156	+ " <td>C4</td>\n",
	157	+ " </tr>\n",
	158	+ " <tr>\n",
	159	+ " <th>5</th>\n",
	160	+ " <td>A5</td>\n",
	161	+ " <td>B5</td>\n",
	162	+ " <td>C5</td>\n",
	163	+ " </tr>\n",
	164	+ " <tr>\n",
	165	+ " <th>6</th>\n",
	166	+ " <td>A6</td>\n",
	167	+ " <td>B6</td>\n",
	168	+ " <td>C6</td>\n",
	169	+ " </tr>\n",
	170	+ " <tr>\n",
	171	+ " <th>7</th>\n",
	172	+ " <td>A7</td>\n",
	173	+ " <td>B7</td>\n",
	174	+ " <td>C7</td>\n",
	175	+ " </tr>\n",
	176	+ " </tbody>\n",
	177	+ "</table>\n",
	178	+ "</div>"
	179	+ ],
	180	+ "text/plain": [
	181	+ " A B C\n",
	182	+ "4 A4 B4 C4\n",
	183	+ "5 A5 B5 C5\n",
	184	+ "6 A6 B6 C6\n",
	185	+ "7 A7 B7 C7"
	186	+ ]
	187	+ },
	188	+ "execution_count": 16,
	189	+ "metadata": {},
	190	+ "output_type": "execute_result"
	191	+ }
	192	+ ],
	193	+ "source": [
	194	+ "df2"
	195	+ ]
	196	+ },
	197	+ {
	198	+ "cell_type": "code",
	199	+ "execution_count": 17,
	200	+ "id": "8a998f5a",
	201	+ "metadata": {},
	202	+ "outputs": [],
	203	+ "source": [
	204	+ "df3 = pd.DataFrame({\n",
	205	+ " 'A':['A8', 'A9', 'A10', 'A11'],\n",
	206	+ " 'B':['B8', 'B9', 'B10', 'B11'],\n",
	207	+ " 'C':['C8', 'C9', 'C10', 'C11']}, index=(8, 9, 10, 11))"
	208	+ ]
	209	+ },
	210	+ {
	211	+ "cell_type": "code",
	212	+ "execution_count": 18,
	213	+ "id": "70f74dd5",
	214	+ "metadata": {},
	215	+ "outputs": [
	216	+ {
	217	+ "data": {
	218	+ "text/html": [
	219	+ "<div>\n",
	220	+ "<style scoped>\n",
	221	+ " .dataframe tbody tr th:only-of-type {\n",
	222	+ " vertical-align: middle;\n",
	223	+ " }\n",
	224	+ "\n",
	225	+ " .dataframe tbody tr th {\n",
	226	+ " vertical-align: top;\n",
	227	+ " }\n",
	228	+ "\n",
	229	+ " .dataframe thead th {\n",
	230	+ " text-align: right;\n",
	231	+ " }\n",
	232	+ "</style>\n",
	233	+ "<table border=\"1\" class=\"dataframe\">\n",
	234	+ " <thead>\n",
	235	+ " <tr style=\"text-align: right;\">\n",
	236	+ " <th></th>\n",
	237	+ " <th>A</th>\n",
	238	+ " <th>B</th>\n",
	239	+ " <th>C</th>\n",
	240	+ " </tr>\n",
	241	+ " </thead>\n",
	242	+ " <tbody>\n",
	243	+ " <tr>\n",
	244	+ " <th>8</th>\n",
	245	+ " <td>A8</td>\n",
	246	+ " <td>B8</td>\n",
	247	+ " <td>C8</td>\n",
	248	+ " </tr>\n",
	249	+ " <tr>\n",
	250	+ " <th>9</th>\n",
	251	+ " <td>A9</td>\n",
	252	+ " <td>B9</td>\n",
	253	+ " <td>C9</td>\n",
	254	+ " </tr>\n",
	255	+ " <tr>\n",
	256	+ " <th>10</th>\n",
	257	+ " <td>A10</td>\n",
	258	+ " <td>B10</td>\n",
	259	+ " <td>C10</td>\n",
	260	+ " </tr>\n",
	261	+ " <tr>\n",
	262	+ " <th>11</th>\n",
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	471	+ "execution_count": 25,
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	749	+ "df4 = pd.DataFrame({\n",
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	751	+ " 'D':['D2', 'D3', 'D6', 'D7'],\n",
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	1232	+ " <th>6</th>\n",
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	1252	+ " A B C D F\n",
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	1263	+ "execution_count": 52,
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	1274	+ "execution_count": 56,
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	1300	+ " <th>B</th>\n",
	1301	+ " <th>C</th>\n",
	1302	+ " <th>B</th>\n",
	1303	+ " <th>D</th>\n",
	1304	+ " <th>F</th>\n",
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	1307	+ " <tbody>\n",
	1308	+ " <tr>\n",
	1309	+ " <th>2</th>\n",
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	1311	+ " <td>B2</td>\n",
	1312	+ " <td>C2</td>\n",
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	1318	+ " <th>3</th>\n",
	1319	+ " <td>A3</td>\n",
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	1321	+ " <td>C3</td>\n",
	1322	+ " <td>B3</td>\n",
	1323	+ " <td>D3</td>\n",
	1324	+ " <td>F3</td>\n",
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	1331	+ " A B C B D F\n",
	1332	+ "2 A2 B2 C2 B2 D2 F2\n",
	1333	+ "3 A3 B3 C3 B3 D3 F3"
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	1336	+ "execution_count": 56,
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	1341	+ "source": [
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	1347	+ "execution_count": 63,
	1348	+ "id": "241cc856",
	1349	+ "metadata": {},
	1350	+ "outputs": [],
	1351	+ "source": [
	1352	+ "left = pd.DataFrame({\n",
	1353	+ " 'key':['K0', 'K4', 'K2', 'K3'],\n",
	1354	+ " 'A':['A0', 'A1', 'A2', 'A3'],\n",
	1355	+ " 'B':['B0', 'B1', 'B2', 'B3']\n",
	1356	+ "})"
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	1359	+ {
	1360	+ "cell_type": "code",
	1361	+ "execution_count": 64,
	1362	+ "id": "7993c237",
	1363	+ "metadata": {},
	1364	+ "outputs": [],
	1365	+ "source": [
	1366	+ "right = pd.DataFrame({\n",
	1367	+ " 'key':['K', 'K1', 'K2', 'K3'],\n",
	1368	+ " 'C':['C0', 'C1', 'C2', 'C3'],\n",
	1369	+ " 'D':['D0', 'D1', 'D2', 'D3']\n",
	1370	+ "})"
	1371	+ ]
	1372	+ },
	1373	+ {
	1374	+ "cell_type": "code",
	1375	+ "execution_count": 65,
	1376	+ "id": "4ea20d17",
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	1397	+ " <thead>\n",
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	1399	+ " <th></th>\n",
	1400	+ " <th>key</th>\n",
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	1402	+ " <th>B</th>\n",
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	1408	+ " <td>K0</td>\n",
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	1410	+ " <td>B0</td>\n",
	1411	+ " </tr>\n",
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20220523/pyplot.ipynb (added)

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