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PedroRamosRguez/gist:2029ae1625844965ce06231462ecf3a9

Created Jul 26, 2019
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"text": [
"\"#pip\" no se reconoce como un comando interno o externo,\n",
"programa o archivo por lotes ejecutable.\n"
]
}
],
"source": [
"!#pip install plotly_express"
]
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"metadata": {},
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"text": [
"\n",
" Each row represents a flower.\n",
"\n",
" https://en.wikipedia.org/wiki/Iris_flower_data_set\n",
"\n",
" Returns:\n",
" A `pandas.DataFrame` with 150 rows and the following columns: `['sepal_length', 'sepal_width', 'petal_length', 'petal_width', 'species',\n",
" 'species_id']`.\n",
" \n"
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" 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>species</th>\n",
" <th>species_id</th>\n",
" </tr>\n",
" </thead>\n",
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" <th>0</th>\n",
" <td>5.1</td>\n",
" <td>3.5</td>\n",
" <td>1.4</td>\n",
" <td>0.2</td>\n",
" <td>setosa</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>4.9</td>\n",
" <td>3.0</td>\n",
" <td>1.4</td>\n",
" <td>0.2</td>\n",
" <td>setosa</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>4.7</td>\n",
" <td>3.2</td>\n",
" <td>1.3</td>\n",
" <td>0.2</td>\n",
" <td>setosa</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4.6</td>\n",
" <td>3.1</td>\n",
" <td>1.5</td>\n",
" <td>0.2</td>\n",
" <td>setosa</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>5.0</td>\n",
" <td>3.6</td>\n",
" <td>1.4</td>\n",
" <td>0.2</td>\n",
" <td>setosa</td>\n",
" <td>1</td>\n",
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"text/plain": [
" sepal_length sepal_width petal_length petal_width species species_id\n",
"0 5.1 3.5 1.4 0.2 setosa 1\n",
"1 4.9 3.0 1.4 0.2 setosa 1\n",
"2 4.7 3.2 1.3 0.2 setosa 1\n",
"3 4.6 3.1 1.5 0.2 setosa 1\n",
"4 5.0 3.6 1.4 0.2 setosa 1"
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import plotly.express as px\n",
"print(px.data.iris.__doc__)\n",
"iris = px.data.iris()\n",
"iris.head()"
]
},
{
"cell_type": "code",
"execution_count": 53,
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],
"source": [
"px.scatter(iris,x='sepal_length',y='sepal_width',color='species', title='Sepal height/widht').update(layout=dict(title=dict(x=0.5)))"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
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