diff --git a/notebooks/jupyter_TP.ipynb b/notebooks/jupyter_TP.ipynb
index ce6afd5ac52e821553139ef77be418f226df68f8..67a96a43f5b91c050fe3da391bb73794d1ef69ad 100644
--- a/notebooks/jupyter_TP.ipynb
+++ b/notebooks/jupyter_TP.ipynb
@@ -2,7 +2,26 @@
"cells": [
{
"cell_type": "markdown",
- "id": "cultural-palestine",
+ "id": "functional-attraction",
+ "metadata": {},
+ "source": [
+ "# <center>**TP**</center>\n",
+ "\n",
+ "<div style=\"text-align:center\">\n",
+ " <img src=\"images/jupyter.png\" width=\"600px\">\n",
+ " <div>\n",
+ " Bertrand Néron, François Laurent, Etienne Kornobis\n",
+ " <br />\n",
+ " <a src=\" https://research.pasteur.fr/en/team/bioinformatics-and-biostatistics-hub/\">Bioinformatics and Biostatistiqucs HUB</a>\n",
+ " <br />\n",
+ " © Institut Pasteur, 2021\n",
+ " </div> \n",
+ "</div>"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "advance-vaccine",
"metadata": {},
"source": [
"# Introduction to JupyterLab\n",
@@ -115,7 +134,7 @@
{
"cell_type": "code",
"execution_count": 13,
- "id": "public-nightlife",
+ "id": "respective-prize",
"metadata": {},
"outputs": [
{
@@ -140,7 +159,7 @@
},
{
"cell_type": "markdown",
- "id": "marine-arctic",
+ "id": "pharmaceutical-college",
"metadata": {},
"source": [
"- The exclamation mark character ``!`` can be used as well to execute the following line in a bash subprocess. For example:"
@@ -149,7 +168,7 @@
{
"cell_type": "code",
"execution_count": 21,
- "id": "considerable-fleet",
+ "id": "drawn-soldier",
"metadata": {},
"outputs": [
{
@@ -166,7 +185,7 @@
},
{
"cell_type": "markdown",
- "id": "satellite-disposal",
+ "id": "natural-submission",
"metadata": {},
"source": [
"- `%timeit` can be used to check for execution times:"
@@ -175,7 +194,7 @@
{
"cell_type": "code",
"execution_count": 18,
- "id": "delayed-thunder",
+ "id": "under-embassy",
"metadata": {},
"outputs": [
{
@@ -192,7 +211,7 @@
},
{
"cell_type": "markdown",
- "id": "vocational-jacksonville",
+ "id": "constant-driving",
"metadata": {},
"source": [
"- Load more extension for the notebook, for example `autoreload` is useful extension to automatically reload a module imported in a Jupyter notebook if the module has changed locally:"
@@ -201,7 +220,7 @@
{
"cell_type": "code",
"execution_count": 22,
- "id": "physical-steering",
+ "id": "waiting-credit",
"metadata": {},
"outputs": [
{
@@ -220,7 +239,7 @@
},
{
"cell_type": "markdown",
- "id": "regular-tiger",
+ "id": "laden-seeker",
"metadata": {},
"source": [
"# Exercices"
@@ -228,7 +247,7 @@
},
{
"cell_type": "markdown",
- "id": "rotary-bouquet",
+ "id": "fitted-insert",
"metadata": {},
"source": [
"The aim here is to get comfortable in Jupyterlab.\n",
@@ -245,14 +264,14 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "chinese-values",
+ "id": "international-thomson",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
- "id": "useful-segment",
+ "id": "olympic-shoot",
"metadata": {},
"source": [
"## Exercise\n",
@@ -268,14 +287,14 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "classical-extraction",
+ "id": "creative-conditioning",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
- "id": "iraqi-wholesale",
+ "id": "bibliographic-concern",
"metadata": {},
"source": [
"## Exercise\n",
@@ -293,14 +312,14 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "refined-relation",
+ "id": "ruled-bottle",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
- "id": "manufactured-treatment",
+ "id": "verbal-field",
"metadata": {},
"source": [
"## Exercise\n",
@@ -317,14 +336,14 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "featured-converter",
+ "id": "identified-calculation",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
- "id": "constant-thriller",
+ "id": "unauthorized-carter",
"metadata": {},
"source": [
"## Exercise\n",
@@ -335,14 +354,14 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "illegal-preserve",
+ "id": "abandoned-shareware",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
- "id": "written-bidding",
+ "id": "molecular-census",
"metadata": {},
"source": [
"## Exercise\n",
@@ -353,14 +372,14 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "waiting-concord",
+ "id": "overall-assurance",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
- "id": "varying-providence",
+ "id": "static-array",
"metadata": {},
"source": [
"# More documentation\n",
diff --git a/notebooks/pandas_TP_solution.ipynb b/notebooks/pandas_TP_solution.ipynb
index ee623af1451cb9e82d3ee8e622a86fe8bbd6560b..42fb09a32044037b6030dac06fcd94a272e538e7 100644
--- a/notebooks/pandas_TP_solution.ipynb
+++ b/notebooks/pandas_TP_solution.ipynb
@@ -2,14 +2,14 @@
"cells": [
{
"cell_type": "markdown",
- "id": "right-artwork",
+ "id": "integral-thermal",
"metadata": {},
"source": [
"# <center>**TP**</center>\n",
"\n",
"<img src=\"./images/pandas_logo.svg\">\n",
"<div style=\"text-align:center\">\n",
- " Bertrand Néron\n",
+ " Bertrand Néron, François Laurent, Etienne Kornobis\n",
" <br />\n",
" <a src=\" https://research.pasteur.fr/en/team/bioinformatics-and-biostatistics-hub/\">Bioinformatics and Biostatistiqucs HUB</a>\n",
" <br />\n",
@@ -19,7 +19,7 @@
},
{
"cell_type": "markdown",
- "id": "sacred-breathing",
+ "id": "trained-fighter",
"metadata": {},
"source": [
"# Exploring Blast results"
@@ -27,7 +27,7 @@
},
{
"cell_type": "markdown",
- "id": "technical-crystal",
+ "id": "manufactured-cursor",
"metadata": {},
"source": [
"- Import the file data/blast.txt into a pandas dataframe variable (named `blast_res`). Verify that its type is a pandas\n",
@@ -40,7 +40,7 @@
{
"cell_type": "code",
"execution_count": 1,
- "id": "recreational-seller",
+ "id": "musical-violence",
"metadata": {},
"outputs": [],
"source": [
@@ -50,7 +50,7 @@
{
"cell_type": "code",
"execution_count": 4,
- "id": "major-dream",
+ "id": "loaded-transfer",
"metadata": {},
"outputs": [],
"source": [
@@ -61,7 +61,7 @@
{
"cell_type": "code",
"execution_count": 5,
- "id": "parliamentary-heaven",
+ "id": "streaming-regulation",
"metadata": {},
"outputs": [
{
@@ -82,7 +82,7 @@
{
"cell_type": "code",
"execution_count": 6,
- "id": "changing-drive",
+ "id": "unsigned-coast",
"metadata": {},
"outputs": [
{
@@ -332,7 +332,7 @@
},
{
"cell_type": "markdown",
- "id": "productive-chorus",
+ "id": "dominant-knowing",
"metadata": {},
"source": [
"Explore ``blast_res`` dataframe:\n",
@@ -346,7 +346,7 @@
{
"cell_type": "code",
"execution_count": 7,
- "id": "yellow-matthew",
+ "id": "simplified-progress",
"metadata": {},
"outputs": [
{
@@ -492,7 +492,7 @@
{
"cell_type": "code",
"execution_count": 8,
- "id": "handled-details",
+ "id": "narrow-smell",
"metadata": {},
"outputs": [
{
@@ -689,7 +689,7 @@
{
"cell_type": "code",
"execution_count": 9,
- "id": "virgin-forestry",
+ "id": "identical-guest",
"metadata": {},
"outputs": [
{
@@ -868,7 +868,7 @@
{
"cell_type": "code",
"execution_count": 10,
- "id": "superb-papua",
+ "id": "alpine-cleveland",
"metadata": {},
"outputs": [
{
@@ -888,7 +888,7 @@
},
{
"cell_type": "markdown",
- "id": "fourth-pennsylvania",
+ "id": "imposed-squad",
"metadata": {},
"source": [
"- Extract 3rd line from the ``blast_res`` dataframe. Which type of data structure is returned by this extraction ?"
@@ -897,7 +897,7 @@
{
"cell_type": "code",
"execution_count": 11,
- "id": "binding-interest",
+ "id": "complicated-football",
"metadata": {},
"outputs": [
{
@@ -930,7 +930,7 @@
{
"cell_type": "code",
"execution_count": 12,
- "id": "careful-dining",
+ "id": "administrative-biodiversity",
"metadata": {},
"outputs": [
{
@@ -950,7 +950,7 @@
},
{
"cell_type": "markdown",
- "id": "common-sixth",
+ "id": "equipped-amendment",
"metadata": {},
"source": [
"- Extract the *sseqid* column from the ``blast_res`` dataframe. "
@@ -959,7 +959,7 @@
{
"cell_type": "code",
"execution_count": 20,
- "id": "located-waters",
+ "id": "seasonal-europe",
"metadata": {},
"outputs": [
{
@@ -994,7 +994,7 @@
},
{
"cell_type": "markdown",
- "id": "searching-coach",
+ "id": "major-leave",
"metadata": {},
"source": [
"- Get the minimum and maximum value of a the *evalue* column."
@@ -1003,7 +1003,7 @@
{
"cell_type": "code",
"execution_count": 21,
- "id": "square-airplane",
+ "id": "varied-influence",
"metadata": {},
"outputs": [
{
@@ -1024,7 +1024,7 @@
{
"cell_type": "code",
"execution_count": 22,
- "id": "innovative-audio",
+ "id": "little-recipient",
"metadata": {},
"outputs": [
{
@@ -1044,7 +1044,7 @@
},
{
"cell_type": "markdown",
- "id": "broad-password",
+ "id": "sitting-blackberry",
"metadata": {},
"source": [
"- Get the median and the mean of the *bitscore* column."
@@ -1053,7 +1053,7 @@
{
"cell_type": "code",
"execution_count": 23,
- "id": "tamil-aggregate",
+ "id": "polyphonic-retro",
"metadata": {},
"outputs": [
{
@@ -1074,7 +1074,7 @@
{
"cell_type": "code",
"execution_count": 24,
- "id": "sitting-metallic",
+ "id": "advisory-symphony",
"metadata": {},
"outputs": [
{
@@ -1094,7 +1094,7 @@
},
{
"cell_type": "markdown",
- "id": "excessive-tournament",
+ "id": "friendly-extra",
"metadata": {},
"source": [
"- Filter in all hits with a percentage of identity (*pident*) superior to 75%."
@@ -1103,7 +1103,7 @@
{
"cell_type": "code",
"execution_count": 25,
- "id": "duplicate-ghana",
+ "id": "rough-globe",
"metadata": {},
"outputs": [
{
@@ -1266,7 +1266,7 @@
{
"cell_type": "code",
"execution_count": 35,
- "id": "developing-browser",
+ "id": "novel-turkey",
"metadata": {},
"outputs": [
{
@@ -1429,7 +1429,7 @@
},
{
"cell_type": "markdown",
- "id": "nonprofit-fitting",
+ "id": "several-light",
"metadata": {},
"source": [
"- Based on the bitscore alone, extract only the best hit(s) (i.e. the highest(s) bitscore(s))."
@@ -1438,7 +1438,7 @@
{
"cell_type": "code",
"execution_count": 26,
- "id": "chronic-wallace",
+ "id": "arbitrary-style",
"metadata": {},
"outputs": [
{
@@ -1518,7 +1518,7 @@
},
{
"cell_type": "markdown",
- "id": "saving-homeless",
+ "id": "heated-poultry",
"metadata": {},
"source": [
"- Filter in all hits which are corresponding to human hits in the database (*sseqid*)."
@@ -1527,7 +1527,7 @@
{
"cell_type": "code",
"execution_count": 28,
- "id": "western-language",
+ "id": "failing-crossing",
"metadata": {},
"outputs": [
{
@@ -1776,7 +1776,7 @@
{
"cell_type": "code",
"execution_count": 29,
- "id": "taken-palmer",
+ "id": "trained-durham",
"metadata": {},
"outputs": [
{
@@ -2025,7 +2025,7 @@
{
"cell_type": "code",
"execution_count": 38,
- "id": "tracked-reform",
+ "id": "structural-hybrid",
"metadata": {},
"outputs": [
{
@@ -2153,7 +2153,7 @@
},
{
"cell_type": "markdown",
- "id": "reliable-dream",
+ "id": "incorporate-interface",
"metadata": {},
"source": [
"- Plot a histogram of the bitscores. "
@@ -2162,7 +2162,7 @@
{
"cell_type": "code",
"execution_count": 32,
- "id": "suspected-substance",
+ "id": "liable-wheat",
"metadata": {},
"outputs": [
{
@@ -2194,7 +2194,7 @@
},
{
"cell_type": "markdown",
- "id": "attempted-development",
+ "id": "reflected-intervention",
"metadata": {},
"source": [
"- Plot a barplot of the number of hits per species (species are considered the last code after the \"_\" in the sseqid column)"
@@ -2203,7 +2203,7 @@
{
"cell_type": "code",
"execution_count": 60,
- "id": "swiss-provider",
+ "id": "normal-glenn",
"metadata": {},
"outputs": [
{
@@ -2323,7 +2323,7 @@
{
"cell_type": "code",
"execution_count": 61,
- "id": "russian-mystery",
+ "id": "arranged-intervention",
"metadata": {},
"outputs": [
{
@@ -2356,7 +2356,7 @@
},
{
"cell_type": "markdown",
- "id": "reliable-shark",
+ "id": "generous-regression",
"metadata": {},
"source": [
"# Extra exercise"
@@ -2365,7 +2365,7 @@
{
"cell_type": "code",
"execution_count": 1,
- "id": "fabulous-endorsement",
+ "id": "experienced-prediction",
"metadata": {},
"outputs": [],
"source": [
@@ -2374,7 +2374,7 @@
},
{
"cell_type": "markdown",
- "id": "boxed-basin",
+ "id": "purple-legend",
"metadata": {},
"source": [
"read the 'data/city_temperature.csv'\n",
@@ -2390,7 +2390,7 @@
{
"cell_type": "code",
"execution_count": 2,
- "id": "positive-gateway",
+ "id": "arctic-pickup",
"metadata": {},
"outputs": [
{
@@ -2409,7 +2409,7 @@
{
"cell_type": "code",
"execution_count": 3,
- "id": "noble-economics",
+ "id": "conventional-section",
"metadata": {},
"outputs": [
{
@@ -2431,7 +2431,7 @@
},
{
"cell_type": "markdown",
- "id": "international-glenn",
+ "id": "authentic-hearts",
"metadata": {},
"source": [
"We will work only on Europe Region. so creat data named europe with only these data"
@@ -2440,7 +2440,7 @@
{
"cell_type": "code",
"execution_count": 4,
- "id": "exciting-founder",
+ "id": "strong-skirt",
"metadata": {},
"outputs": [],
"source": [
@@ -2449,7 +2449,7 @@
},
{
"cell_type": "markdown",
- "id": "dressed-carbon",
+ "id": "protected-desperate",
"metadata": {},
"source": [
"wich country are in europe?"
@@ -2458,7 +2458,7 @@
{
"cell_type": "code",
"execution_count": 5,
- "id": "crude-pillow",
+ "id": "unable-establishment",
"metadata": {},
"outputs": [
{
@@ -2484,7 +2484,7 @@
},
{
"cell_type": "markdown",
- "id": "dated-guest",
+ "id": "engaged-republican",
"metadata": {},
"source": [
"remove columns 'Region' and 'State' from the data"
@@ -2493,7 +2493,7 @@
{
"cell_type": "code",
"execution_count": 6,
- "id": "valued-minutes",
+ "id": "anticipated-illinois",
"metadata": {},
"outputs": [],
"source": [
@@ -2502,7 +2502,7 @@
},
{
"cell_type": "markdown",
- "id": "million-blank",
+ "id": "amino-grant",
"metadata": {},
"source": [
"from europe data create a new dataset containing countries: 'France', 'Spain', 'Italy'"
@@ -2511,7 +2511,7 @@
{
"cell_type": "code",
"execution_count": 7,
- "id": "textile-proof",
+ "id": "organized-tender",
"metadata": {},
"outputs": [],
"source": [
@@ -2520,7 +2520,7 @@
},
{
"cell_type": "markdown",
- "id": "statutory-hierarchy",
+ "id": "endangered-weekly",
"metadata": {},
"source": [
"group the data on 'City' and 'Year' compute the mean of each group and keep only the 'AvgTemperature' column."
@@ -2529,7 +2529,7 @@
{
"cell_type": "code",
"execution_count": 8,
- "id": "induced-finish",
+ "id": "sacred-secret",
"metadata": {},
"outputs": [
{
@@ -2562,7 +2562,7 @@
},
{
"cell_type": "markdown",
- "id": "bibliographic-bidding",
+ "id": "north-condition",
"metadata": {},
"source": [
"do the same but compute the standard deviation"
@@ -2571,7 +2571,7 @@
{
"cell_type": "code",
"execution_count": 9,
- "id": "valued-smooth",
+ "id": "absent-envelope",
"metadata": {},
"outputs": [
{
@@ -2604,7 +2604,7 @@
},
{
"cell_type": "markdown",
- "id": "outdoor-content",
+ "id": "continued-tiger",
"metadata": {},
"source": [
"* reset the index fo the mean data and std data\n",
@@ -2615,7 +2615,7 @@
{
"cell_type": "code",
"execution_count": 10,
- "id": "dangerous-republican",
+ "id": "geological-newman",
"metadata": {},
"outputs": [],
"source": [
@@ -2627,7 +2627,7 @@
},
{
"cell_type": "markdown",
- "id": "equivalent-grove",
+ "id": "ongoing-armenia",
"metadata": {},
"source": [
"merge the two table data_mean and data_std"
@@ -2636,7 +2636,7 @@
{
"cell_type": "code",
"execution_count": 11,
- "id": "appreciated-europe",
+ "id": "liquid-brighton",
"metadata": {},
"outputs": [
{
@@ -2778,7 +2778,7 @@
},
{
"cell_type": "markdown",
- "id": "asian-evanescence",
+ "id": "egyptian-restoration",
"metadata": {},
"source": [
"save the data in a file"
@@ -2787,7 +2787,7 @@
{
"cell_type": "code",
"execution_count": 12,
- "id": "analyzed-beaver",
+ "id": "agreed-diesel",
"metadata": {},
"outputs": [],
"source": [
@@ -2796,7 +2796,7 @@
},
{
"cell_type": "markdown",
- "id": "elect-percentage",
+ "id": "interim-interstate",
"metadata": {},
"source": [
"# Teasing\n",
@@ -2807,7 +2807,7 @@
{
"cell_type": "code",
"execution_count": 13,
- "id": "beneficial-coordinator",
+ "id": "animated-alert",
"metadata": {},
"outputs": [
{
@@ -2903,7 +2903,7 @@
{
"cell_type": "code",
"execution_count": null,
- "id": "neither-popularity",
+ "id": "random-mediterranean",
"metadata": {},
"outputs": [],
"source": []