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" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row66\" class=\"row_heading level0 row66\" >66</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row66_col0\" class=\"data row66 col0\" >tn24c</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row66_col1\" class=\"data row66 col1\" >Température minimale sur 24 heures (°C)</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row66_col2\" class=\"data row66 col2\" >29165</td>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row67\" class=\"row_heading level0 row67\" >67</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row67_col0\" class=\"data row67 col0\" >tx12c</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row67_col1\" class=\"data row67 col1\" >Température maximale sur 12 heures (°C)</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row67_col2\" class=\"data row67 col2\" >21883</td>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row68\" class=\"row_heading level0 row68\" >68</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row68_col0\" class=\"data row68 col0\" >tx24c</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row68_col1\" class=\"data row68 col1\" >Température maximale sur 24 heures (°C)</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row68_col2\" class=\"data row68 col2\" >29165</td>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row69\" class=\"row_heading level0 row69\" >69</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row69_col0\" class=\"data row69 col0\" >tminsolc</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row69_col1\" class=\"data row69 col1\" >Température minimale du sol sur 12 heures (en °C)</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row69_col2\" class=\"data row69 col2\" >27364</td>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row70\" class=\"row_heading level0 row70\" >70</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row70_col0\" class=\"data row70 col0\" >altitude</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row70_col1\" class=\"data row70 col1\" >Altitude</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row70_col2\" class=\"data row70 col2\" >0</td>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row71\" class=\"row_heading level0 row71\" >71</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row71_col0\" class=\"data row71 col0\" >longitude</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row71_col1\" class=\"data row71 col1\" >Longitude</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row71_col2\" class=\"data row71 col2\" >0</td>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row72\" class=\"row_heading level0 row72\" >72</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row72_col0\" class=\"data row72 col0\" >latitude</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row72_col1\" class=\"data row72 col1\" >Latitude</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row72_col2\" class=\"data row72 col2\" >0</td>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row73\" class=\"row_heading level0 row73\" >73</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row73_col0\" class=\"data row73 col0\" >libgeo</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row73_col1\" class=\"data row73 col1\" >communes (name)</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row73_col2\" class=\"data row73 col2\" >0</td>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row74\" class=\"row_heading level0 row74\" >74</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row74_col0\" class=\"data row74 col0\" >codegeo</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row74_col1\" class=\"data row74 col1\" >communes (code)</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row74_col2\" class=\"data row74 col2\" >0</td>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row75\" class=\"row_heading level0 row75\" >75</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row75_col0\" class=\"data row75 col0\" >nom_epci</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row75_col1\" class=\"data row75 col1\" >EPCI (name)</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row75_col2\" class=\"data row75 col2\" >0</td>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row76\" class=\"row_heading level0 row76\" >76</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row76_col0\" class=\"data row76 col0\" >code_epci</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row76_col1\" class=\"data row76 col1\" >EPCI (code)</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row76_col2\" class=\"data row76 col2\" >0</td>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row77\" class=\"row_heading level0 row77\" >77</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row77_col0\" class=\"data row77 col0\" >nom_dept</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row77_col1\" class=\"data row77 col1\" >department (name)</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row77_col2\" class=\"data row77 col2\" >0</td>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row78\" class=\"row_heading level0 row78\" >78</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row78_col0\" class=\"data row78 col0\" >code_dep</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row78_col1\" class=\"data row78 col1\" >department (code)</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row78_col2\" class=\"data row78 col2\" >0</td>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row79\" class=\"row_heading level0 row79\" >79</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row79_col0\" class=\"data row79 col0\" >nom_reg</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row79_col1\" class=\"data row79 col1\" >region (name)</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row79_col2\" class=\"data row79 col2\" >0</td>\n",
" <th id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3level0_row80\" class=\"row_heading level0 row80\" >80</th>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row80_col0\" class=\"data row80 col0\" >code_reg</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row80_col1\" class=\"data row80 col1\" >region (code)</td>\n",
" <td id=\"T_a0099504_41de_11eb_aa99_e3cf125b8da3row80_col2\" class=\"data row80 col2\" >0</td>\n",
" </tr>\n",
" </tbody></table>"
],
"text/plain": [
"<pandas.io.formats.style.Styler at 0x7f79fa772ed0>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Shape is : (29165, 81)\n"
]
}
],
"source": [
"df = pd.read_csv(f'{datasets_dir}/SYNOP/{data_filename}', header=0, sep=';')\n",
"pwk.subtitle('Raw data :')\n",
"display(df.tail(10))\n",
"\n",
"# ---- Get the columns name as descriptions\n",
"synop_desc = list(df.columns)\n",
"\n",
"# ---- Set Codes as columns name\n",
"df.columns = synop_codes\n",
"code2desc = dict(zip(synop_codes, synop_desc))\n",
"\n",
"# ---- Count the na values by columns\n",
"columns_na = df.isna().sum().tolist()\n",
"\n",
"# ---- Show all of that\n",
"df_desc=pd.DataFrame({'Code':synop_codes, 'Description':synop_desc, 'Na':columns_na})\n",
"\n",
"pwk.subtitle('List of columns :')\n",
"display(df_desc.style.set_properties(**{'text-align': 'left'}))\n",
"\n",
"print('Shape is : ', df.shape)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Step 3 - Keep only certain columns"
]
},
{
"cell_type": "code",
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"metadata": {},
"outputs": [
{
"data": {
"text/markdown": [
"<br>**Our selected columns :**"
],
"text/plain": [
"<IPython.core.display.Markdown object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"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>date</th>\n",
" <th>pmer</th>\n",
" <th>tend</th>\n",
" <th>cod_tend</th>\n",
" <th>dd</th>\n",
" <th>ff</th>\n",
" <th>td</th>\n",
" <th>u</th>\n",
" <th>ww</th>\n",
" <th>pres</th>\n",
" <th>rafper</th>\n",
" <th>per</th>\n",
" <th>rr1</th>\n",
" <th>rr3</th>\n",
" <th>tc</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2015-06-12T17:00:00+02:00</td>\n",
" <td>101050.0</td>\n",
" <td>-230.0</td>\n",
" <td>6.0</td>\n",
" <td>140.0</td>\n",
" <td>3.6</td>\n",
" <td>286.25</td>\n",
" <td>50.0</td>\n",
" <td>2.0</td>\n",
" <td>98330.0</td>\n",
" <td>5.1</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>-0.1</td>\n",
" <td>24.2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2015-06-05T17:00:00+02:00</td>\n",
" <td>101590.0</td>\n",
" <td>-220.0</td>\n",
" <td>8.0</td>\n",
" <td>190.0</td>\n",
" <td>3.9</td>\n",
" <td>286.95</td>\n",
" <td>32.0</td>\n",
" <td>3.0</td>\n",
" <td>98930.0</td>\n",
" <td>9.9</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>32.6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2015-06-15T11:00:00+02:00</td>\n",
" <td>101420.0</td>\n",
" <td>90.0</td>\n",
" <td>1.0</td>\n",
" <td>270.0</td>\n",
" <td>1.5</td>\n",
" <td>286.85</td>\n",
" <td>64.0</td>\n",
" <td>3.0</td>\n",
" <td>98660.0</td>\n",
" <td>4.5</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>20.8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2015-06-15T14:00:00+02:00</td>\n",
" <td>101430.0</td>\n",
" <td>20.0</td>\n",
" <td>1.0</td>\n",
" <td>10.0</td>\n",
" <td>2.5</td>\n",
" <td>286.45</td>\n",
" <td>55.0</td>\n",
" <td>1.0</td>\n",
" <td>98680.0</td>\n",
" <td>5.1</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>22.8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2015-06-20T05:00:00+02:00</td>\n",
" <td>102030.0</td>\n",
" <td>0.0</td>\n",
" <td>4.0</td>\n",
" <td>50.0</td>\n",
" <td>0.7</td>\n",
" <td>282.95</td>\n",
" <td>82.0</td>\n",
" <td>2.0</td>\n",
" <td>99170.0</td>\n",
" <td>2.4</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>12.8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>2015-06-22T05:00:00+02:00</td>\n",
" <td>101680.0</td>\n",
" <td>-120.0</td>\n",
" <td>6.0</td>\n",
" <td>180.0</td>\n",
" <td>0.7</td>\n",
" <td>286.15</td>\n",
" <td>80.0</td>\n",
" <td>1.0</td>\n",
" <td>98870.0</td>\n",
" <td>4.7</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>-0.1</td>\n",
" <td>16.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>2015-06-23T02:00:00+02:00</td>\n",
" <td>101270.0</td>\n",
" <td>150.0</td>\n",
" <td>2.0</td>\n",
" <td>20.0</td>\n",
" <td>4.5</td>\n",
" <td>282.95</td>\n",
" <td>54.0</td>\n",
" <td>0.0</td>\n",
" <td>98490.0</td>\n",
" <td>10.2</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>19.3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>2015-06-25T14:00:00+02:00</td>\n",
" <td>102180.0</td>\n",
" <td>-40.0</td>\n",
" <td>8.0</td>\n",
" <td>10.0</td>\n",
" <td>2.3</td>\n",
" <td>283.25</td>\n",
" <td>38.0</td>\n",
" <td>1.0</td>\n",
" <td>99430.0</td>\n",
" <td>7.5</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>25.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>2015-07-05T20:00:00+02:00</td>\n",
" <td>101410.0</td>\n",
" <td>50.0</td>\n",
" <td>3.0</td>\n",
" <td>190.0</td>\n",
" <td>8.3</td>\n",
" <td>288.05</td>\n",
" <td>33.0</td>\n",
" <td>3.0</td>\n",
" <td>98760.0</td>\n",
" <td>13.4</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>33.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>2015-05-14T17:00:00+02:00</td>\n",
" <td>101070.0</td>\n",
" <td>-150.0</td>\n",
" <td>6.0</td>\n",
" <td>20.0</td>\n",
" <td>6.2</td>\n",
" <td>284.95</td>\n",
" <td>60.0</td>\n",
" <td>3.0</td>\n",
" <td>98300.0</td>\n",
" <td>11.1</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>19.8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>2015-03-16T22:00:00+01:00</td>\n",
" <td>102150.0</td>\n",
" <td>40.0</td>\n",
" <td>1.0</td>\n",
" <td>50.0</td>\n",
" <td>1.7</td>\n",
" <td>275.05</td>\n",
" <td>62.0</td>\n",
" <td>1.0</td>\n",
" <td>99240.0</td>\n",
" <td>4.6</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>8.8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>2015-03-26T01:00:00+01:00</td>\n",
" <td>101140.0</td>\n",
" <td>100.0</td>\n",
" <td>1.0</td>\n",
" <td>330.0</td>\n",
" <td>5.9</td>\n",
" <td>275.45</td>\n",
" <td>82.0</td>\n",
" <td>1.0</td>\n",
" <td>98220.0</td>\n",
" <td>8.1</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>5.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>2015-04-03T17:00:00+02:00</td>\n",
" <td>101690.0</td>\n",
" <td>-250.0</td>\n",
" <td>7.0</td>\n",
" <td>340.0</td>\n",
" <td>3.5</td>\n",
" <td>278.15</td>\n",
" <td>55.0</td>\n",
" <td>1.0</td>\n",
" <td>98850.0</td>\n",
" <td>6.4</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>13.9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>2015-04-05T20:00:00+02:00</td>\n",
" <td>101850.0</td>\n",
" <td>140.0</td>\n",
" <td>3.0</td>\n",
" <td>10.0</td>\n",
" <td>7.8</td>\n",
" <td>268.45</td>\n",
" <td>38.0</td>\n",
" <td>1.0</td>\n",
" <td>98950.0</td>\n",
" <td>13.5</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>8.9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>2014-10-22T17:00:00+02:00</td>\n",
" <td>102670.0</td>\n",
" <td>-70.0</td>\n",
" <td>8.0</td>\n",
" <td>20.0</td>\n",
" <td>4.6</td>\n",
" <td>275.35</td>\n",
" <td>55.0</td>\n",
" <td>1.0</td>\n",
" <td>99770.0</td>\n",
" <td>7.2</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>10.9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>2015-02-08T16:00:00+01:00</td>\n",
" <td>102570.0</td>\n",
" <td>20.0</td>\n",
" <td>3.0</td>\n",
" <td>350.0</td>\n",
" <td>12.3</td>\n",
" <td>271.55</td>\n",
" <td>68.0</td>\n",
" <td>0.0</td>\n",
" <td>99590.0</td>\n",
" <td>19.9</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>3.8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>2015-02-11T07:00:00+01:00</td>\n",
" <td>102670.0</td>\n",
" <td>-10.0</td>\n",
" <td>7.0</td>\n",
" <td>290.0</td>\n",
" <td>2.0</td>\n",
" <td>267.55</td>\n",
" <td>88.0</td>\n",
" <td>10.0</td>\n",
" <td>99610.0</td>\n",
" <td>3.3</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>-3.9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>2015-02-07T04:00:00+01:00</td>\n",
" <td>101900.0</td>\n",
" <td>160.0</td>\n",
" <td>1.0</td>\n",
" <td>310.0</td>\n",
" <td>2.0</td>\n",
" <td>268.65</td>\n",
" <td>74.0</td>\n",
" <td>2.0</td>\n",
" <td>98900.0</td>\n",
" <td>3.2</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>-0.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>2015-02-13T04:00:00+01:00</td>\n",
" <td>102140.0</td>\n",
" <td>-50.0</td>\n",
" <td>8.0</td>\n",
" <td>140.0</td>\n",
" <td>2.1</td>\n",
" <td>273.55</td>\n",
" <td>74.0</td>\n",
" <td>0.0</td>\n",
" <td>99190.0</td>\n",
" <td>4.9</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>4.6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>2015-02-16T19:00:00+01:00</td>\n",
" <td>102060.0</td>\n",
" <td>100.0</td>\n",
" <td>3.0</td>\n",
" <td>20.0</td>\n",
" <td>3.2</td>\n",
" <td>275.65</td>\n",
" <td>88.0</td>\n",
" <td>1.0</td>\n",
" <td>99110.0</td>\n",
" <td>5.1</td>\n",
" <td>-10.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>4.3</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" date pmer tend cod_tend dd ff td \\\n",
"0 2015-06-12T17:00:00+02:00 101050.0 -230.0 6.0 140.0 3.6 286.25 \n",
"1 2015-06-05T17:00:00+02:00 101590.0 -220.0 8.0 190.0 3.9 286.95 \n",
"2 2015-06-15T11:00:00+02:00 101420.0 90.0 1.0 270.0 1.5 286.85 \n",
"3 2015-06-15T14:00:00+02:00 101430.0 20.0 1.0 10.0 2.5 286.45 \n",
"4 2015-06-20T05:00:00+02:00 102030.0 0.0 4.0 50.0 0.7 282.95 \n",
"5 2015-06-22T05:00:00+02:00 101680.0 -120.0 6.0 180.0 0.7 286.15 \n",
"6 2015-06-23T02:00:00+02:00 101270.0 150.0 2.0 20.0 4.5 282.95 \n",
"7 2015-06-25T14:00:00+02:00 102180.0 -40.0 8.0 10.0 2.3 283.25 \n",
"8 2015-07-05T20:00:00+02:00 101410.0 50.0 3.0 190.0 8.3 288.05 \n",
"9 2015-05-14T17:00:00+02:00 101070.0 -150.0 6.0 20.0 6.2 284.95 \n",
"10 2015-03-16T22:00:00+01:00 102150.0 40.0 1.0 50.0 1.7 275.05 \n",
"11 2015-03-26T01:00:00+01:00 101140.0 100.0 1.0 330.0 5.9 275.45 \n",
"12 2015-04-03T17:00:00+02:00 101690.0 -250.0 7.0 340.0 3.5 278.15 \n",
"13 2015-04-05T20:00:00+02:00 101850.0 140.0 3.0 10.0 7.8 268.45 \n",
"14 2014-10-22T17:00:00+02:00 102670.0 -70.0 8.0 20.0 4.6 275.35 \n",
"15 2015-02-08T16:00:00+01:00 102570.0 20.0 3.0 350.0 12.3 271.55 \n",
"16 2015-02-11T07:00:00+01:00 102670.0 -10.0 7.0 290.0 2.0 267.55 \n",
"17 2015-02-07T04:00:00+01:00 101900.0 160.0 1.0 310.0 2.0 268.65 \n",
"18 2015-02-13T04:00:00+01:00 102140.0 -50.0 8.0 140.0 2.1 273.55 \n",
"19 2015-02-16T19:00:00+01:00 102060.0 100.0 3.0 20.0 3.2 275.65 \n",
"\n",
" u ww pres rafper per rr1 rr3 tc \n",
"0 50.0 2.0 98330.0 5.1 -10.0 0.0 -0.1 24.2 \n",
"1 32.0 3.0 98930.0 9.9 -10.0 0.0 0.0 32.6 \n",
"2 64.0 3.0 98660.0 4.5 -10.0 0.0 0.0 20.8 \n",
"3 55.0 1.0 98680.0 5.1 -10.0 0.0 0.0 22.8 \n",
"4 82.0 2.0 99170.0 2.4 -10.0 0.0 0.0 12.8 \n",
"5 80.0 1.0 98870.0 4.7 -10.0 0.0 -0.1 16.5 \n",
"6 54.0 0.0 98490.0 10.2 -10.0 0.0 0.0 19.3 \n",
"7 38.0 1.0 99430.0 7.5 -10.0 0.0 0.0 25.5 \n",
"8 33.0 3.0 98760.0 13.4 -10.0 0.0 0.0 33.4 \n",
"9 60.0 3.0 98300.0 11.1 -10.0 0.0 0.0 19.8 \n",
"10 62.0 1.0 99240.0 4.6 -10.0 0.0 0.0 8.8 \n",
"11 82.0 1.0 98220.0 8.1 -10.0 0.0 0.0 5.1 \n",
"12 55.0 1.0 98850.0 6.4 -10.0 0.0 0.0 13.9 \n",
"13 38.0 1.0 98950.0 13.5 -10.0 0.0 0.0 8.9 \n",
"14 55.0 1.0 99770.0 7.2 -10.0 0.0 0.0 10.9 \n",
"15 68.0 0.0 99590.0 19.9 -10.0 0.0 0.0 3.8 \n",
"16 88.0 10.0 99610.0 3.3 -10.0 0.0 0.0 -3.9 \n",
"17 74.0 2.0 98900.0 3.2 -10.0 0.0 0.0 -0.4 \n",
"18 74.0 0.0 99190.0 4.9 -10.0 0.0 0.0 4.6 \n",
"19 88.0 1.0 99110.0 5.1 -10.0 0.0 0.0 4.3 "
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/markdown": [
"<br>**Few statistics :**"
],
"text/plain": [
"<IPython.core.display.Markdown object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>pmer</th>\n",
" <th>tend</th>\n",
" <th>cod_tend</th>\n",
" <th>dd</th>\n",
" <th>ff</th>\n",
" <th>td</th>\n",
" <th>u</th>\n",
" <th>ww</th>\n",
" <th>pres</th>\n",
" <th>rafper</th>\n",
" <th>per</th>\n",
" <th>rr1</th>\n",
" <th>rr3</th>\n",
" <th>tc</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>29148.000000</td>\n",
" <td>29163.000000</td>\n",
" <td>29163.000000</td>\n",
" <td>29162.000000</td>\n",
" <td>29163.00000</td>\n",
" <td>29148.000000</td>\n",
" <td>29148.000000</td>\n",
" <td>29164.000000</td>\n",
" <td>29165.000000</td>\n",
" <td>29156.000000</td>\n",
" <td>29157.0</td>\n",
" <td>29070.000000</td>\n",
" <td>29092.000000</td>\n",
" <td>29151.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>101753.552902</td>\n",
" <td>0.255118</td>\n",
" <td>4.306930</td>\n",
" <td>204.088197</td>\n",
" <td>3.39653</td>\n",
" <td>280.027865</td>\n",
" <td>71.021614</td>\n",
" <td>10.106158</td>\n",
" <td>98894.598320</td>\n",
" <td>6.299005</td>\n",
" <td>-10.0</td>\n",
" <td>0.092886</td>\n",
" <td>0.279008</td>\n",
" <td>12.688261</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>798.093804</td>\n",
" <td>111.438232</td>\n",
" <td>2.716149</td>\n",
" <td>115.422508</td>\n",
" <td>2.46898</td>\n",
" <td>5.857534</td>\n",
" <td>18.275755</td>\n",
" <td>19.404573</td>\n",
" <td>761.586766</td>\n",
" <td>3.852478</td>\n",
" <td>0.0</td>\n",
" <td>0.605673</td>\n",
" <td>1.414611</td>\n",
" <td>8.146390</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>97960.000000</td>\n",
" <td>-750.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.00000</td>\n",
" <td>249.250000</td>\n",
" <td>2.000000</td>\n",
" <td>0.000000</td>\n",
" <td>95170.000000</td>\n",
" <td>0.000000</td>\n",
" <td>-10.0</td>\n",
" <td>-0.100000</td>\n",
" <td>-0.100000</td>\n",
" <td>-12.100000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>101300.000000</td>\n",
" <td>-70.000000</td>\n",
" <td>2.000000</td>\n",
" <td>130.000000</td>\n",
" <td>1.50000</td>\n",
" <td>275.825000</td>\n",
" <td>58.000000</td>\n",
" <td>2.000000</td>\n",
" <td>98480.000000</td>\n",
" <td>3.600000</td>\n",
" <td>-10.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>6.600000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>101740.000000</td>\n",
" <td>0.000000</td>\n",
" <td>3.000000</td>\n",
" <td>190.000000</td>\n",
" <td>2.90000</td>\n",
" <td>280.250000</td>\n",
" <td>74.000000</td>\n",
" <td>2.000000</td>\n",
" <td>98920.000000</td>\n",
" <td>5.300000</td>\n",
" <td>-10.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>12.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>102240.000000</td>\n",
" <td>70.000000</td>\n",
" <td>7.000000</td>\n",
" <td>330.000000</td>\n",
" <td>4.60000</td>\n",
" <td>284.550000</td>\n",
" <td>86.000000</td>\n",
" <td>3.000000</td>\n",
" <td>99360.000000</td>\n",
" <td>8.200000</td>\n",
" <td>-10.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>18.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>104280.000000</td>\n",
" <td>810.000000</td>\n",
" <td>8.000000</td>\n",
" <td>360.000000</td>\n",
" <td>18.80000</td>\n",
" <td>295.950000</td>\n",
" <td>100.000000</td>\n",
" <td>97.000000</td>\n",
" <td>101210.000000</td>\n",
" <td>30.200000</td>\n",
" <td>-10.0</td>\n",
" <td>19.000000</td>\n",
" <td>45.000000</td>\n",
" <td>38.900000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" pmer tend cod_tend dd ff \\\n",
"count 29148.000000 29163.000000 29163.000000 29162.000000 29163.00000 \n",
"mean 101753.552902 0.255118 4.306930 204.088197 3.39653 \n",
"std 798.093804 111.438232 2.716149 115.422508 2.46898 \n",
"min 97960.000000 -750.000000 0.000000 0.000000 0.00000 \n",
"25% 101300.000000 -70.000000 2.000000 130.000000 1.50000 \n",
"50% 101740.000000 0.000000 3.000000 190.000000 2.90000 \n",
"75% 102240.000000 70.000000 7.000000 330.000000 4.60000 \n",
"max 104280.000000 810.000000 8.000000 360.000000 18.80000 \n",
"\n",
" td u ww pres rafper \\\n",
"count 29148.000000 29148.000000 29164.000000 29165.000000 29156.000000 \n",
"mean 280.027865 71.021614 10.106158 98894.598320 6.299005 \n",
"std 5.857534 18.275755 19.404573 761.586766 3.852478 \n",
"min 249.250000 2.000000 0.000000 95170.000000 0.000000 \n",
"25% 275.825000 58.000000 2.000000 98480.000000 3.600000 \n",
"50% 280.250000 74.000000 2.000000 98920.000000 5.300000 \n",
"75% 284.550000 86.000000 3.000000 99360.000000 8.200000 \n",
"max 295.950000 100.000000 97.000000 101210.000000 30.200000 \n",
"\n",
" per rr1 rr3 tc \n",
"count 29157.0 29070.000000 29092.000000 29151.000000 \n",
"mean -10.0 0.092886 0.279008 12.688261 \n",
"std 0.0 0.605673 1.414611 8.146390 \n",
"min -10.0 -0.100000 -0.100000 -12.100000 \n",
"25% -10.0 0.000000 0.000000 6.600000 \n",
"50% -10.0 0.000000 0.000000 12.500000 \n",
"75% -10.0 0.000000 0.000000 18.500000 \n",
"max -10.0 19.000000 45.000000 38.900000 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"columns_used=['date','pmer','tend','cod_tend','dd','ff','td','u','ww','pres','rafper','per','rr1','rr3','tc']\n",
"\n",
"# ---- Drop unused columns\n",
"\n",
"to_drop = df.columns.difference(columns_used)\n",
"df.drop( to_drop, axis=1, inplace=True)\n",
"\n",
"# ---- Show all of that\n",
"\n",
"pwk.subtitle('Our selected columns :')\n",
"pwk.subtitle('Few statistics :')\n",
"display(df.describe())\n",
"\n",
"# ---- 'per' column is constant, we can drop it\n",
"\n",
"df.drop(['per'],axis=1,inplace=True)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Step 4 - Cleanup session : Let's sort it and cook up some NaN values"
]
},
{
"cell_type": "code",
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"metadata": {},
"outputs": [
{
"data": {
"text/markdown": [
"<br>**Before :**"
],
"text/plain": [
"<IPython.core.display.Markdown object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\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>date</th>\n",
" <th>pmer</th>\n",
" <th>tend</th>\n",
" <th>cod_tend</th>\n",
" <th>dd</th>\n",
" <th>ff</th>\n",
" <th>td</th>\n",
" <th>u</th>\n",
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" <th>tc</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>396</th>\n",
" <td>2010-02-19T16:00:00+01:00</td>\n",
" <td>99760.0</td>\n",
" <td>180.0</td>\n",
" <td>3.0</td>\n",
" <td>330.0</td>\n",
" <td>4.6</td>\n",
" <td>275.85</td>\n",
" <td>79.0</td>\n",
" <td>21.0</td>\n",
" <td>96890.0</td>\n",
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" <td>0.0</td>\n",
" <td>1.0</td>\n",
" <td>6.1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>434</th>\n",
" <td>2010-02-24T10:00:00+01:00</td>\n",
" <td>100310.0</td>\n",
" <td>60.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>279.25</td>\n",
" <td>77.0</td>\n",
" <td>2.0</td>\n",
" <td>97470.0</td>\n",
" <td>NaN</td>\n",
" <td>0.2</td>\n",
" <td>0.2</td>\n",
" <td>9.9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>477</th>\n",
" <td>2010-03-01T19:00:00+01:00</td>\n",
" <td>101400.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>340.0</td>\n",
" <td>2.6</td>\n",
" <td>275.45</td>\n",
" <td>61.0</td>\n",
" <td>2.0</td>\n",
" <td>98520.0</td>\n",
" <td>5.7</td>\n",
" <td>0.0</td>\n",
" <td>NaN</td>\n",
" <td>9.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>734</th>\n",
" <td>2010-04-03T02:00:00+02:00</td>\n",
" <td>101550.0</td>\n",
" <td>50.0</td>\n",
" <td>0.0</td>\n",
" <td>190.0</td>\n",
" <td>7.7</td>\n",
" <td>277.55</td>\n",
" <td>64.0</td>\n",
" <td>2.0</td>\n",
" <td>98680.0</td>\n",
" <td>12.3</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>10.9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1061</th>\n",
" <td>2010-05-13T23:00:00+02:00</td>\n",
" <td>NaN</td>\n",
" <td>60.0</td>\n",
" <td>2.0</td>\n",
" <td>330.0</td>\n",
" <td>4.6</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2.0</td>\n",
" <td>98220.0</td>\n",
" <td>7.7</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>9.9</td>\n",