Commit 389d2d5f by Paktalin

Section 3 done

parent b86bbb5b
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"X = []"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
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"array([[1.79302012e+01, 9.45205920e+01, 3.20259530e+02],\n",
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" [4.14266940e+00, 5.22547264e+01, 1.68034401e+02]])"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"for line in open(\"data_2d.csv\"):\n",
" row = line.split(',')\n",
" # print(row)\n",
" sample = list(map(float, row))\n",
" X.append(sample)\n",
"X = np.array(X)\n",
"X"
]
}
],
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"name": "python3"
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"pandas.core.frame.DataFrame"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
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],
"source": [
"X = pd.read_csv(\"data_2d.csv\", header=None)\n",
"type(X)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 100 entries, 0 to 99\n",
"Data columns (total 3 columns):\n",
"0 100 non-null float64\n",
"1 100 non-null float64\n",
"2 100 non-null float64\n",
"dtypes: float64(3)\n",
"memory usage: 2.4 KB\n"
]
}
],
"source": [
"X.info()"
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},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
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"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"X.head(10)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Index(['Month', 'International airline passengers: monthly totals in thousands. Jan 49 ? Dec 60'], dtype='object')"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df = pd.read_csv(\"international-airline-passengers.csv\", engine=\"python\", skipfooter=3)\n",
"df.columns"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Index(['month', 'passengers'], dtype='object')"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.columns = [\"month\", \"passengers\"]\n",
"df.columns"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
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"Name: passengers, Length: 144, dtype: int64"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df['passengers']"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
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"122 406\n",
"123 396\n",
"124 420\n",
"125 472\n",
"126 548\n",
"127 559\n",
"128 463\n",
"129 407\n",
"130 362\n",
"131 405\n",
"132 417\n",
"133 391\n",
"134 419\n",
"135 461\n",
"136 472\n",
"137 535\n",
"138 622\n",
"139 606\n",
"140 508\n",
"141 461\n",
"142 390\n",
"143 432\n",
"Name: passengers, Length: 144, dtype: int64"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.passengers"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
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" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
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" .dataframe thead th {\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>month</th>\n",
" <th>passengers</th>\n",
" <th>ones</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1949-01</td>\n",
" <td>112</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1949-02</td>\n",
" <td>118</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>1949-03</td>\n",
" <td>132</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>1949-04</td>\n",
" <td>129</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>1949-05</td>\n",
" <td>121</td>\n",
" <td>1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" month passengers ones\n",
"0 1949-01 112 1\n",
"1 1949-02 118 1\n",
"2 1949-03 132 1\n",
"3 1949-04 129 1\n",
"4 1949-05 121 1"
]
},
"execution_count": 9,
"metadata": {},
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}
],
"source": [
"df['ones'] = 1\n",
"df.head()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
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"Month","International airline passengers: monthly totals in thousands. Jan 49 ? Dec 60"
"1949-01",112
"1949-02",118
"1949-03",132
"1949-04",129
"1949-05",121
"1949-06",135
"1949-07",148
"1949-08",148
"1949-09",136
"1949-10",119
"1949-11",104
"1949-12",118
"1950-01",115
"1950-02",126
"1950-03",141
"1950-04",135
"1950-05",125
"1950-06",149
"1950-07",170
"1950-08",170
"1950-09",158
"1950-10",133
"1950-11",114
"1950-12",140
"1951-01",145
"1951-02",150
"1951-03",178
"1951-04",163
"1951-05",172
"1951-06",178
"1951-07",199
"1951-08",199
"1951-09",184
"1951-10",162
"1951-11",146
"1951-12",166
"1952-01",171
"1952-02",180
"1952-03",193
"1952-04",181
"1952-05",183
"1952-06",218
"1952-07",230
"1952-08",242
"1952-09",209
"1952-10",191
"1952-11",172
"1952-12",194
"1953-01",196
"1953-02",196
"1953-03",236
"1953-04",235
"1953-05",229
"1953-06",243
"1953-07",264
"1953-08",272
"1953-09",237
"1953-10",211
"1953-11",180
"1953-12",201
"1954-01",204
"1954-02",188
"1954-03",235
"1954-04",227
"1954-05",234
"1954-06",264
"1954-07",302
"1954-08",293
"1954-09",259
"1954-10",229
"1954-11",203
"1954-12",229
"1955-01",242
"1955-02",233
"1955-03",267
"1955-04",269
"1955-05",270
"1955-06",315
"1955-07",364
"1955-08",347
"1955-09",312
"1955-10",274
"1955-11",237
"1955-12",278
"1956-01",284
"1956-02",277
"1956-03",317
"1956-04",313
"1956-05",318
"1956-06",374
"1956-07",413
"1956-08",405
"1956-09",355
"1956-10",306
"1956-11",271
"1956-12",306
"1957-01",315
"1957-02",301
"1957-03",356
"1957-04",348
"1957-05",355
"1957-06",422
"1957-07",465
"1957-08",467
"1957-09",404
"1957-10",347
"1957-11",305
"1957-12",336
"1958-01",340
"1958-02",318
"1958-03",362
"1958-04",348
"1958-05",363
"1958-06",435
"1958-07",491
"1958-08",505
"1958-09",404
"1958-10",359
"1958-11",310
"1958-12",337
"1959-01",360
"1959-02",342
"1959-03",406
"1959-04",396
"1959-05",420
"1959-06",472
"1959-07",548
"1959-08",559
"1959-09",463
"1959-10",407
"1959-11",362
"1959-12",405
"1960-01",417
"1960-02",391
"1960-03",419
"1960-04",461
"1960-05",472
"1960-06",535
"1960-07",622
"1960-08",606
"1960-09",508
"1960-10",461
"1960-11",390
"1960-12",432
International airline passengers: monthly totals in thousands. Jan 49 ? Dec 60
user_id,email,age
1,alice@gmail.com,20
2,bob@gmail.com,25
3,carol@gmail.com,30
\ No newline at end of file
user_id,ad_id,click
1,1,1
1,2,0
1,5,0
2,3,0
2,4,1
2,1,0
3,2,0
3,1,0
3,3,0
3,4,0
3,5,1
\ No newline at end of file
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