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146 | 146 | "# Add basin data to ib_wmo\n",
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147 | 147 | "ib_wmo[\"basin\"] = huracanpy.utils.get_basin(ib_wmo.lon, ib_wmo.lat)\n",
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148 | 148 | "# Match tracks between ib_wmo and ib_usa, then retrieve LMI\n",
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149 |
| - "m = huracanpy.assess.match(ib_wmo, ib_usa, \"wmo\", \"usa\")\n", |
| 149 | + "m = huracanpy.assess.match([ib_wmo, ib_usa], names=[\"wmo\", \"usa\"])\n", |
150 | 150 | "max_winds = m.join(\n",
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151 |
| - " ib_wmo.groupby(\"track_id\").max()[[\"wind\", \"basin\"]].to_dataframe(), on=\"id_wmo\"\n", |
| 151 | + " ib_wmo[[\"wind\"]].groupby(ib_wmo.track_id).max().to_dataframe(), on=\"id_wmo\"\n", |
152 | 152 | ").join(\n",
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153 |
| - " ib_usa.groupby(\"track_id\").max().wind.to_dataframe(),\n", |
| 153 | + " ib_usa[[\"wind\"]].groupby(ib_usa.track_id).max().to_dataframe(),\n", |
154 | 154 | " on=\"id_usa\",\n",
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155 | 155 | " lsuffix=\"_wmo\",\n",
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156 | 156 | " rsuffix=\"_usa\",\n",
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157 | 157 | ")"
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158 | 158 | ]
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159 | 159 | },
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| 160 | + { |
| 161 | + "cell_type": "code", |
| 162 | + "execution_count": null, |
| 163 | + "id": "bb31f486-51a4-4c49-b1ad-d67569ec9a6a", |
| 164 | + "metadata": {}, |
| 165 | + "outputs": [], |
| 166 | + "source": [ |
| 167 | + "# Add basin with separate groupby\n", |
| 168 | + "max_winds = max_winds.join(\n", |
| 169 | + " ib_wmo[[\"basin\"]].groupby(ib_wmo.track_id).first().to_dataframe(),\n", |
| 170 | + " on=\"id_wmo\"\n", |
| 171 | + ")" |
| 172 | + ] |
| 173 | + }, |
160 | 174 | {
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161 | 175 | "cell_type": "code",
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162 | 176 | "execution_count": null,
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