Replace 05-NumPy&Pandas.ipynb

parent 5f95bdb9
...@@ -2052,7 +2052,7 @@ ...@@ -2052,7 +2052,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 64, "execution_count": 11,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
...@@ -2137,7 +2137,7 @@ ...@@ -2137,7 +2137,7 @@
"4 5.0 3.6 1.4 0.2 setosa" "4 5.0 3.6 1.4 0.2 setosa"
] ]
}, },
"execution_count": 64, "execution_count": 11,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
...@@ -2145,7 +2145,7 @@ ...@@ -2145,7 +2145,7 @@
"source": [ "source": [
"import numpy as np\n", "import numpy as np\n",
"import pandas as pd\n", "import pandas as pd\n",
"iris = pd.read_csv('data/iris.csv')\n", "iris = pd.read_csv('iris/iris.csv')\n",
"iris.head()" "iris.head()"
] ]
}, },
...@@ -2158,10 +2158,24 @@ ...@@ -2158,10 +2158,24 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 16,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [
"source": [] {
"data": {
"text/plain": [
"150"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len ( iris )\n",
"iris.shape[0]\n"
]
}, },
{ {
"cell_type": "markdown", "cell_type": "markdown",
...@@ -2172,10 +2186,23 @@ ...@@ -2172,10 +2186,23 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 17,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [
"source": [] {
"data": {
"text/plain": [
"5"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"iris.shape[1]"
]
}, },
{ {
"cell_type": "markdown", "cell_type": "markdown",
...@@ -2186,10 +2213,56 @@ ...@@ -2186,10 +2213,56 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 24,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [
"source": [] {
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"text/plain": [
"Empty DataFrame\n",
"Columns: [sepal_length, sepal_width, petal_length, petal_width, species]\n",
"Index: []"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"iris[:0]"
]
}, },
{ {
"cell_type": "markdown", "cell_type": "markdown",
...@@ -2200,10 +2273,23 @@ ...@@ -2200,10 +2273,23 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 28,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [
"source": [] {
"data": {
"text/plain": [
"'species'"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"iris.columns[4]"
]
}, },
{ {
"cell_type": "markdown", "cell_type": "markdown",
...@@ -2214,10 +2300,81 @@ ...@@ -2214,10 +2300,81 @@
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"text/plain": [
" sepal_length petal_length\n",
"0 5.1 1.4\n",
"1 4.9 1.4\n",
"2 4.7 1.3\n",
"3 4.6 1.5\n",
"4 5.0 1.4"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
" iris [ [ \"sepal_length\" , \"petal_length\" ] ] . head ( )"
]
}, },
{ {
"cell_type": "markdown", "cell_type": "markdown",
...@@ -2228,10 +2385,99 @@ ...@@ -2228,10 +2385,99 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
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"text/plain": [
" sepal_length sepal_width petal_length petal_width species\n",
"0 5.1 3.5 1.4 0.2 setosa\n",
"1 4.9 3.0 1.4 0.2 setosa\n",
"4 5.0 3.6 1.4 0.2 setosa\n",
"5 5.4 3.9 1.7 0.4 setosa\n",
"7 5.0 3.4 1.5 0.2 setosa"
]
},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"iris [iris.sepal_length > 4.8].head()"
]
}, },
{ {
"cell_type": "markdown", "cell_type": "markdown",
...@@ -2242,10 +2488,732 @@ ...@@ -2242,10 +2488,732 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 38,
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" <td>0.52</td>\n",
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" <td>setosa</td>\n",
" <td>0.51</td>\n",
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" <td>0.45</td>\n",
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" <td>0.34</td>\n",
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" <td>setosa</td>\n",
" <td>0.60</td>\n",
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" <td>setosa</td>\n",
" <td>0.85</td>\n",
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" <td>4.8</td>\n",
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" <td>1.9</td>\n",
" <td>0.2</td>\n",
" <td>setosa</td>\n",
" <td>0.38</td>\n",
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" <td>5.0</td>\n",
" <td>3.0</td>\n",
" <td>1.6</td>\n",
" <td>0.2</td>\n",
" <td>setosa</td>\n",
" <td>0.32</td>\n",
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" <td>5.0</td>\n",
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" <td>0.64</td>\n",
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" <td>5.2</td>\n",
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" <td>setosa</td>\n",
" <td>0.30</td>\n",
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" <td>setosa</td>\n",
" <td>0.28</td>\n",
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" <td>virginica</td>\n",
" <td>13.11</td>\n",
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" <td>5.6</td>\n",
" <td>2.8</td>\n",
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" <td>virginica</td>\n",
" <td>9.80</td>\n",
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" <td>7.7</td>\n",
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" <td>13.40</td>\n",
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" <td>6.3</td>\n",
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" <td>virginica</td>\n",
" <td>8.82</td>\n",
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" <td>6.7</td>\n",
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" <td>11.97</td>\n",
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" <td>7.2</td>\n",
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" <td>6.2</td>\n",
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" <td>8.64</td>\n",
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" <th>127</th>\n",
" <td>6.1</td>\n",
" <td>3.0</td>\n",
" <td>4.9</td>\n",
" <td>1.8</td>\n",
" <td>virginica</td>\n",
" <td>8.82</td>\n",
" </tr>\n",
" <tr>\n",
" <th>128</th>\n",
" <td>6.4</td>\n",
" <td>2.8</td>\n",
" <td>5.6</td>\n",
" <td>2.1</td>\n",
" <td>virginica</td>\n",
" <td>11.76</td>\n",
" </tr>\n",
" <tr>\n",
" <th>129</th>\n",
" <td>7.2</td>\n",
" <td>3.0</td>\n",
" <td>5.8</td>\n",
" <td>1.6</td>\n",
" <td>virginica</td>\n",
" <td>9.28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>130</th>\n",
" <td>7.4</td>\n",
" <td>2.8</td>\n",
" <td>6.1</td>\n",
" <td>1.9</td>\n",
" <td>virginica</td>\n",
" <td>11.59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>131</th>\n",
" <td>7.9</td>\n",
" <td>3.8</td>\n",
" <td>6.4</td>\n",
" <td>2.0</td>\n",
" <td>virginica</td>\n",
" <td>12.80</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132</th>\n",
" <td>6.4</td>\n",
" <td>2.8</td>\n",
" <td>5.6</td>\n",
" <td>2.2</td>\n",
" <td>virginica</td>\n",
" <td>12.32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>133</th>\n",
" <td>6.3</td>\n",
" <td>2.8</td>\n",
" <td>5.1</td>\n",
" <td>1.5</td>\n",
" <td>virginica</td>\n",
" <td>7.65</td>\n",
" </tr>\n",
" <tr>\n",
" <th>134</th>\n",
" <td>6.1</td>\n",
" <td>2.6</td>\n",
" <td>5.6</td>\n",
" <td>1.4</td>\n",
" <td>virginica</td>\n",
" <td>7.84</td>\n",
" </tr>\n",
" <tr>\n",
" <th>135</th>\n",
" <td>7.7</td>\n",
" <td>3.0</td>\n",
" <td>6.1</td>\n",
" <td>2.3</td>\n",
" <td>virginica</td>\n",
" <td>14.03</td>\n",
" </tr>\n",
" <tr>\n",
" <th>136</th>\n",
" <td>6.3</td>\n",
" <td>3.4</td>\n",
" <td>5.6</td>\n",
" <td>2.4</td>\n",
" <td>virginica</td>\n",
" <td>13.44</td>\n",
" </tr>\n",
" <tr>\n",
" <th>137</th>\n",
" <td>6.4</td>\n",
" <td>3.1</td>\n",
" <td>5.5</td>\n",
" <td>1.8</td>\n",
" <td>virginica</td>\n",
" <td>9.90</td>\n",
" </tr>\n",
" <tr>\n",
" <th>138</th>\n",
" <td>6.0</td>\n",
" <td>3.0</td>\n",
" <td>4.8</td>\n",
" <td>1.8</td>\n",
" <td>virginica</td>\n",
" <td>8.64</td>\n",
" </tr>\n",
" <tr>\n",
" <th>139</th>\n",
" <td>6.9</td>\n",
" <td>3.1</td>\n",
" <td>5.4</td>\n",
" <td>2.1</td>\n",
" <td>virginica</td>\n",
" <td>11.34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>140</th>\n",
" <td>6.7</td>\n",
" <td>3.1</td>\n",
" <td>5.6</td>\n",
" <td>2.4</td>\n",
" <td>virginica</td>\n",
" <td>13.44</td>\n",
" </tr>\n",
" <tr>\n",
" <th>141</th>\n",
" <td>6.9</td>\n",
" <td>3.1</td>\n",
" <td>5.1</td>\n",
" <td>2.3</td>\n",
" <td>virginica</td>\n",
" <td>11.73</td>\n",
" </tr>\n",
" <tr>\n",
" <th>142</th>\n",
" <td>5.8</td>\n",
" <td>2.7</td>\n",
" <td>5.1</td>\n",
" <td>1.9</td>\n",
" <td>virginica</td>\n",
" <td>9.69</td>\n",
" </tr>\n",
" <tr>\n",
" <th>143</th>\n",
" <td>6.8</td>\n",
" <td>3.2</td>\n",
" <td>5.9</td>\n",
" <td>2.3</td>\n",
" <td>virginica</td>\n",
" <td>13.57</td>\n",
" </tr>\n",
" <tr>\n",
" <th>144</th>\n",
" <td>6.7</td>\n",
" <td>3.3</td>\n",
" <td>5.7</td>\n",
" <td>2.5</td>\n",
" <td>virginica</td>\n",
" <td>14.25</td>\n",
" </tr>\n",
" <tr>\n",
" <th>145</th>\n",
" <td>6.7</td>\n",
" <td>3.0</td>\n",
" <td>5.2</td>\n",
" <td>2.3</td>\n",
" <td>virginica</td>\n",
" <td>11.96</td>\n",
" </tr>\n",
" <tr>\n",
" <th>146</th>\n",
" <td>6.3</td>\n",
" <td>2.5</td>\n",
" <td>5.0</td>\n",
" <td>1.9</td>\n",
" <td>virginica</td>\n",
" <td>9.50</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147</th>\n",
" <td>6.5</td>\n",
" <td>3.0</td>\n",
" <td>5.2</td>\n",
" <td>2.0</td>\n",
" <td>virginica</td>\n",
" <td>10.40</td>\n",
" </tr>\n",
" <tr>\n",
" <th>148</th>\n",
" <td>6.2</td>\n",
" <td>3.4</td>\n",
" <td>5.4</td>\n",
" <td>2.3</td>\n",
" <td>virginica</td>\n",
" <td>12.42</td>\n",
" </tr>\n",
" <tr>\n",
" <th>149</th>\n",
" <td>5.9</td>\n",
" <td>3.0</td>\n",
" <td>5.1</td>\n",
" <td>1.8</td>\n",
" <td>virginica</td>\n",
" <td>9.18</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>150 rows × 6 columns</p>\n",
"</div>"
],
"text/plain": [
" sepal_length sepal_width petal_length petal_width species \\\n",
"0 5.1 3.5 1.4 0.2 setosa \n",
"1 4.9 3.0 1.4 0.2 setosa \n",
"2 4.7 3.2 1.3 0.2 setosa \n",
"3 4.6 3.1 1.5 0.2 setosa \n",
"4 5.0 3.6 1.4 0.2 setosa \n",
"5 5.4 3.9 1.7 0.4 setosa \n",
"6 4.6 3.4 1.4 0.3 setosa \n",
"7 5.0 3.4 1.5 0.2 setosa \n",
"8 4.4 2.9 1.4 0.2 setosa \n",
"9 4.9 3.1 1.5 0.1 setosa \n",
"10 5.4 3.7 1.5 0.2 setosa \n",
"11 4.8 3.4 1.6 0.2 setosa \n",
"12 4.8 3.0 1.4 0.1 setosa \n",
"13 4.3 3.0 1.1 0.1 setosa \n",
"14 5.8 4.0 1.2 0.2 setosa \n",
"15 5.7 4.4 1.5 0.4 setosa \n",
"16 5.4 3.9 1.3 0.4 setosa \n",
"17 5.1 3.5 1.4 0.3 setosa \n",
"18 5.7 3.8 1.7 0.3 setosa \n",
"19 5.1 3.8 1.5 0.3 setosa \n",
"20 5.4 3.4 1.7 0.2 setosa \n",
"21 5.1 3.7 1.5 0.4 setosa \n",
"22 4.6 3.6 1.0 0.2 setosa \n",
"23 5.1 3.3 1.7 0.5 setosa \n",
"24 4.8 3.4 1.9 0.2 setosa \n",
"25 5.0 3.0 1.6 0.2 setosa \n",
"26 5.0 3.4 1.6 0.4 setosa \n",
"27 5.2 3.5 1.5 0.2 setosa \n",
"28 5.2 3.4 1.4 0.2 setosa \n",
"29 4.7 3.2 1.6 0.2 setosa \n",
".. ... ... ... ... ... \n",
"120 6.9 3.2 5.7 2.3 virginica \n",
"121 5.6 2.8 4.9 2.0 virginica \n",
"122 7.7 2.8 6.7 2.0 virginica \n",
"123 6.3 2.7 4.9 1.8 virginica \n",
"124 6.7 3.3 5.7 2.1 virginica \n",
"125 7.2 3.2 6.0 1.8 virginica \n",
"126 6.2 2.8 4.8 1.8 virginica \n",
"127 6.1 3.0 4.9 1.8 virginica \n",
"128 6.4 2.8 5.6 2.1 virginica \n",
"129 7.2 3.0 5.8 1.6 virginica \n",
"130 7.4 2.8 6.1 1.9 virginica \n",
"131 7.9 3.8 6.4 2.0 virginica \n",
"132 6.4 2.8 5.6 2.2 virginica \n",
"133 6.3 2.8 5.1 1.5 virginica \n",
"134 6.1 2.6 5.6 1.4 virginica \n",
"135 7.7 3.0 6.1 2.3 virginica \n",
"136 6.3 3.4 5.6 2.4 virginica \n",
"137 6.4 3.1 5.5 1.8 virginica \n",
"138 6.0 3.0 4.8 1.8 virginica \n",
"139 6.9 3.1 5.4 2.1 virginica \n",
"140 6.7 3.1 5.6 2.4 virginica \n",
"141 6.9 3.1 5.1 2.3 virginica \n",
"142 5.8 2.7 5.1 1.9 virginica \n",
"143 6.8 3.2 5.9 2.3 virginica \n",
"144 6.7 3.3 5.7 2.5 virginica \n",
"145 6.7 3.0 5.2 2.3 virginica \n",
"146 6.3 2.5 5.0 1.9 virginica \n",
"147 6.5 3.0 5.2 2.0 virginica \n",
"148 6.2 3.4 5.4 2.3 virginica \n",
"149 5.9 3.0 5.1 1.8 virginica \n",
"\n",
" multiplicacion \n",
"0 0.28 \n",
"1 0.28 \n",
"2 0.26 \n",
"3 0.30 \n",
"4 0.28 \n",
"5 0.68 \n",
"6 0.42 \n",
"7 0.30 \n",
"8 0.28 \n",
"9 0.15 \n",
"10 0.30 \n",
"11 0.32 \n",
"12 0.14 \n",
"13 0.11 \n",
"14 0.24 \n",
"15 0.60 \n",
"16 0.52 \n",
"17 0.42 \n",
"18 0.51 \n",
"19 0.45 \n",
"20 0.34 \n",
"21 0.60 \n",
"22 0.20 \n",
"23 0.85 \n",
"24 0.38 \n",
"25 0.32 \n",
"26 0.64 \n",
"27 0.30 \n",
"28 0.28 \n",
"29 0.32 \n",
".. ... \n",
"120 13.11 \n",
"121 9.80 \n",
"122 13.40 \n",
"123 8.82 \n",
"124 11.97 \n",
"125 10.80 \n",
"126 8.64 \n",
"127 8.82 \n",
"128 11.76 \n",
"129 9.28 \n",
"130 11.59 \n",
"131 12.80 \n",
"132 12.32 \n",
"133 7.65 \n",
"134 7.84 \n",
"135 14.03 \n",
"136 13.44 \n",
"137 9.90 \n",
"138 8.64 \n",
"139 11.34 \n",
"140 13.44 \n",
"141 11.73 \n",
"142 9.69 \n",
"143 13.57 \n",
"144 14.25 \n",
"145 11.96 \n",
"146 9.50 \n",
"147 10.40 \n",
"148 12.42 \n",
"149 9.18 \n",
"\n",
"[150 rows x 6 columns]"
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
" iris [ \"multiplicacion\" ] = iris [ \"petal_length\" ] * iris [ \"petal_width\" ] \n",
"iris"
]
}, },
{ {
"cell_type": "markdown", "cell_type": "markdown",
...@@ -2256,10 +3224,96 @@ ...@@ -2256,10 +3224,96 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 41,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [
"source": [] {
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>sepal_length</th>\n",
" <th>sepal_width</th>\n",
" <th>petal_length</th>\n",
" <th>petal_width</th>\n",
" <th>multiplicacion</th>\n",
" </tr>\n",
" <tr>\n",
" <th>species</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>setosa</th>\n",
" <td>5.006</td>\n",
" <td>3.428</td>\n",
" <td>1.462</td>\n",
" <td>0.246</td>\n",
" <td>0.3656</td>\n",
" </tr>\n",
" <tr>\n",
" <th>versicolor</th>\n",
" <td>5.936</td>\n",
" <td>2.770</td>\n",
" <td>4.260</td>\n",
" <td>1.326</td>\n",
" <td>5.7204</td>\n",
" </tr>\n",
" <tr>\n",
" <th>virginica</th>\n",
" <td>6.588</td>\n",
" <td>2.974</td>\n",
" <td>5.552</td>\n",
" <td>2.026</td>\n",
" <td>11.2962</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" sepal_length sepal_width petal_length petal_width \\\n",
"species \n",
"setosa 5.006 3.428 1.462 0.246 \n",
"versicolor 5.936 2.770 4.260 1.326 \n",
"virginica 6.588 2.974 5.552 2.026 \n",
"\n",
" multiplicacion \n",
"species \n",
"setosa 0.3656 \n",
"versicolor 5.7204 \n",
"virginica 11.2962 "
]
},
"execution_count": 41,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"iris . groupby ( 'species' ) . mean ( )"
]
} }
], ],
"metadata": { "metadata": {
......
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