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[FIX] Colab-flag #349

Merged
merged 28 commits into from
May 14, 2024
Merged

[FIX] Colab-flag #349

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40136fa
try_with_not_run_colab
elephaint May 8, 2024
5019ac1
try_not_in_colab
elephaint May 8, 2024
baf36d6
not_run_in_colab
elephaint May 8, 2024
7d3da4f
fix_tutorials
elephaint May 8, 2024
12479fe
Tutorials 1-10 compatible with Colab
marcopeix May 8, 2024
754c4f9
Merge branch 'feature/colab-in-utils' into feature/colab-notebooks
elephaint May 8, 2024
0c73a2d
add_colab_badge_and_colab_flag
elephaint May 8, 2024
c43acf9
refactoring_comments_azul
elephaint May 9, 2024
35a9f03
Merge branch 'main' into feature/colab-notebooks
elephaint May 9, 2024
5f043eb
Merge branch 'main' into feature/colab-notebooks
elephaint May 9, 2024
3a9b9d1
Tutorials 1-10 compatible with Colab
marcopeix May 8, 2024
3ba3b37
try_with_not_run_colab
elephaint May 8, 2024
a8633d9
try_not_in_colab
elephaint May 8, 2024
96ca249
not_run_in_colab
elephaint May 8, 2024
0d43e73
fix_tutorials
elephaint May 8, 2024
1f59a9d
add_colab_badge_and_colab_flag
elephaint May 8, 2024
4aaa236
refactoring_comments_azul
elephaint May 9, 2024
5be6740
try_install_at_top
elephaint May 10, 2024
67cf4fd
fix_conflicts
elephaint May 10, 2024
701df6a
remove_logs
elephaint May 10, 2024
11cca66
fix_all_badges
elephaint May 10, 2024
e94ff6f
fix_first_cell_hide
elephaint May 10, 2024
b0f9f47
try_new_pip_cell
elephaint May 10, 2024
f0c465c
fix_first_cell
elephaint May 10, 2024
e283f21
fix_links_in_badges
elephaint May 10, 2024
1f35beb
pip
elephaint May 13, 2024
3618ef3
Merge branch 'main' into feature/colab-notebooks
elephaint May 13, 2024
e696685
merge_main_and_fix_errors_in_conflict_notebooks
elephaint May 13, 2024
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82 changes: 69 additions & 13 deletions nbs/docs/capabilities/anomaly-detection/01_quickstart.ipynb
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72 changes: 70 additions & 2 deletions nbs/docs/capabilities/anomaly-detection/02_anomaly_exogenous.ipynb
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86 changes: 69 additions & 17 deletions nbs/docs/capabilities/anomaly-detection/03_anomaly_detection_date_features.ipynb
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81 changes: 69 additions & 12 deletions nbs/docs/capabilities/anomaly-detection/04_confidence_levels.ipynb
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88 changes: 69 additions & 19 deletions nbs/docs/capabilities/forecast/01_quickstart.ipynb
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79 changes: 68 additions & 11 deletions nbs/docs/capabilities/forecast/02_exogenous_variables.ipynb
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Original file line number Diff line number Diff line change
@@ -1,5 +1,47 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#| hide\n",
"!pip install -Uqq nixtla"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#| hide \n",
"from nixtla.utils import in_colab"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#| hide \n",
"IN_COLAB = in_colab()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#| hide\n",
"if not IN_COLAB:\n",
" from nixtla.utils import colab_badge\n",
" from dotenv import load_dotenv"
]
},
{
"cell_type": "markdown",
"metadata": {},
Expand All @@ -13,10 +55,25 @@
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"outputs": [
{
"data": {
"text/markdown": [
"[![](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Nixtla/nixtla/blob/main/nbs/docs/capabilities/forecast/02_exogenous_variables.ipynb)"
],
"text/plain": [
"<IPython.core.display.Markdown object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import pandas as pd\n",
"from nixtla import NixtlaClient"
"#| echo: false\n",
"if not IN_COLAB:\n",
" load_dotenv()\n",
" colab_badge('docs/capabilities/forecast/02_exogenous_variables')"
]
},
{
Expand All @@ -25,10 +82,8 @@
"metadata": {},
"outputs": [],
"source": [
"nixtla_client = NixtlaClient(\n",
" # defaults to os.environ.get(\"NIXTLA_API_KEY\")\n",
" api_key = 'my_api_key_provided_by_nixtla'\n",
")"
"import pandas as pd\n",
"from nixtla import NixtlaClient"
]
},
{
Expand All @@ -37,8 +92,10 @@
"metadata": {},
"outputs": [],
"source": [
"#| hide\n",
"from dotenv import load_dotenv"
"nixtla_client = NixtlaClient(\n",
" # defaults to os.environ.get(\"NIXTLA_API_KEY\")\n",
" api_key = 'my_api_key_provided_by_nixtla'\n",
")"
]
},
{
Expand All @@ -48,8 +105,8 @@
"outputs": [],
"source": [
"#| hide\n",
"load_dotenv()\n",
"nixtla_client = NixtlaClient()"
"if not IN_COLAB:\n",
" nixtla_client = NixtlaClient()"
]
},
{
Expand Down
91 changes: 68 additions & 23 deletions nbs/docs/capabilities/forecast/03_holidays_special_dates.ipynb
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Original file line number Diff line number Diff line change
@@ -1,12 +1,13 @@
{
"cells": [
{
"cell_type": "markdown",
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Add holidays and special dates\n",
"\n",
"You can create DataFrames specifying holidays for particular countries and specify your own special dates to include them as features for forecasting."
"#| hide\n",
"!pip install -Uqq nixtla"
]
},
{
Expand All @@ -15,10 +16,8 @@
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"from nixtla import NixtlaClient\n",
"from nixtla.date_features import CountryHolidays\n",
"from nixtla.date_features import SpecialDates"
"#| hide \n",
"from nixtla.utils import in_colab"
]
},
{
Expand All @@ -27,10 +26,8 @@
"metadata": {},
"outputs": [],
"source": [
"nixtla_client = NixtlaClient(\n",
" # defaults to os.environ.get(\"NIXTLA_API_KEY\")\n",
" api_key = 'my_api_key_provided_by_nixtla'\n",
")"
"#| hide \n",
"IN_COLAB = in_colab()"
]
},
{
Expand All @@ -40,7 +37,43 @@
"outputs": [],
"source": [
"#| hide\n",
"from dotenv import load_dotenv"
"if not IN_COLAB:\n",
" from nixtla.utils import colab_badge\n",
" from dotenv import load_dotenv"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Add holidays and special dates\n",
"\n",
"You can create DataFrames specifying holidays for particular countries and specify your own special dates to include them as features for forecasting."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"data": {
"text/markdown": [
"[![](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Nixtla/nixtla/blob/main/nbs/docs/capabilities/forecast/03_holidays_special_dates.ipynb)"
],
"text/plain": [
"<IPython.core.display.Markdown object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#| echo: false\n",
"if not IN_COLAB:\n",
" load_dotenv()\n",
" colab_badge('docs/capabilities/forecast/03_holidays_special_dates')"
]
},
{
Expand All @@ -49,16 +82,33 @@
"metadata": {},
"outputs": [],
"source": [
"#| hide\n",
"load_dotenv()\n",
"nixtla_client = NixtlaClient()"
"import pandas as pd\n",
"from nixtla import NixtlaClient\n",
"from nixtla.date_features import CountryHolidays\n",
"from nixtla.date_features import SpecialDates"
]
},
{
"cell_type": "markdown",
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"## Step 2: Get country holidays"
"nixtla_client = NixtlaClient(\n",
" # defaults to os.environ.get(\"NIXTLA_API_KEY\")\n",
" api_key = 'my_api_key_provided_by_nixtla'\n",
")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#| hide\n",
"if not IN_COLAB:\n",
" nixtla_client = NixtlaClient()"
]
},
{
Expand Down Expand Up @@ -91,11 +141,6 @@
"source": [
"For a detailed guide on using special dates and holidays, read our tutorial on [Holidays and special dates](https://docs.nixtla.io/docs/tutorials-holidays_and_special_dates)."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": []
}
],
"metadata": {
Expand Down
87 changes: 70 additions & 17 deletions nbs/docs/capabilities/forecast/04_categorical_variables.ipynb
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Original file line number Diff line number Diff line change
@@ -1,5 +1,47 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#| hide\n",
"!pip install -Uqq nixtla"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#| hide \n",
"from nixtla.utils import in_colab"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#| hide \n",
"IN_COLAB = in_colab()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#| hide\n",
"if not IN_COLAB:\n",
" from nixtla.utils import colab_badge\n",
" from dotenv import load_dotenv"
]
},
{
"cell_type": "markdown",
"metadata": {},
Expand All @@ -9,6 +51,31 @@
"TimeGPT supports categorical variables and we can create them using `SpecialDates`."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"data": {
"text/markdown": [
"[![](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Nixtla/nixtla/blob/main/nbs/docs/capabilities/forecast/04_categorical_variables.ipynb)"
],
"text/plain": [
"<IPython.core.display.Markdown object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"#| echo: false\n",
"if not IN_COLAB:\n",
" load_dotenv()\n",
" colab_badge('docs/capabilities/forecast/04_categorical_variables')"
]
},
{
"cell_type": "code",
"execution_count": null,
Expand Down Expand Up @@ -40,18 +107,8 @@
"outputs": [],
"source": [
"#| hide\n",
"from dotenv import load_dotenv"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#| hide\n",
"load_dotenv()\n",
"nixtla_client = NixtlaClient()"
"if not IN_COLAB:\n",
" nixtla_client = NixtlaClient()"
]
},
{
Expand All @@ -66,6 +123,7 @@
"INFO:nixtla.nixtla_client:Validating inputs...\n",
"INFO:nixtla.nixtla_client:Preprocessing dataframes...\n",
"INFO:nixtla.nixtla_client:Inferred freq: MS\n",
"WARNING:nixtla.nixtla_client:You did not provide X_df. Exogenous variables in df are ignored. To surpress this warning, please add X_df with exogenous variables: christmas_vacations, summer_vacations\n",
"WARNING:nixtla.nixtla_client:The specified horizon \"h\" exceeds the model horizon. This may lead to less accurate forecasts. Please consider using a smaller horizon.\n",
"INFO:nixtla.nixtla_client:Restricting input...\n",
"INFO:nixtla.nixtla_client:Calling Forecast Endpoint...\n"
Expand Down Expand Up @@ -106,11 +164,6 @@
"source": [
"For a detailed guide on using categorical variables for forecasting, read our in-depth tutorial on [Categorical variables](https://docs.nixtla.io/docs/tutorials-categorical_variables)."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": []
}
],
"metadata": {
Expand Down
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