From 5d3d8f312548296d118447e40c81fd481e6239b5 Mon Sep 17 00:00:00 2001 From: Sykarim06 Date: Thu, 1 May 2025 23:09:34 -0400 Subject: [PATCH 1/4] Submitting Assignment 1 --- 02_activities/assignments/assignment_1.ipynb | 157 +++++++++++++++++-- 1 file changed, 143 insertions(+), 14 deletions(-) diff --git a/02_activities/assignments/assignment_1.ipynb b/02_activities/assignments/assignment_1.ipynb index bd82b6b8b..9277a3a88 100644 --- a/02_activities/assignments/assignment_1.ipynb +++ b/02_activities/assignments/assignment_1.ipynb @@ -40,7 +40,7 @@ "source": [ "### Part 1: Building the base Anagram Checker\n", "\n", - "Given two valid strings, check to see if they are anagrams of each other. If it is, return `True`, else `False`. For this part, we can assume that uppercase letters are the same as if it was a lowercase character.\n", + "Given two valid strings, check to see if they are anagrams of each other. If it is, return `True`, else `False`. For this part, we can assume that case letters are the same as if it was a lowercase character.\n", "\n", "Examples of anagrams:\n", "* Silent and Listen\n", @@ -58,30 +58,117 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\n", + "# In this example we don't care about the case sensitivity, hence we will convert all the text to lower casefold/caseless matching\n", + "\n", + "# Approach: I am thinking about folding, sorting the string, and then comparing strings. If these are really anagrams:\n", + "# Once sorted they should ideally be the same string representation\n", + "\n", + "# We should also handle for string length difference because in that situation, those are not really anagrams.\n", + "\n", + "def anagram_checker(word_a, word_b):\n", + " word_a_fold = word_a.casefold()\n", + " word_b_fold = word_b.casefold()\n", + "\n", + " # Check lengths first because if not, these are not anagrams\n", + " if len(word_a_fold) != len(word_b_fold):\n", + " print(f'Sorry! The words \"{word_a}\" and \"{word_b}\" are NOT anagrams — their lengths differ.')\n", + " return False\n", + " # Compare sorted versions\n", + " if sorted(word_a_fold) == sorted(word_b_fold):\n", + " print(f'Great job! The words \"{word_a}\" and \"{word_b}\" are anagrams.')\n", + " return True\n", + " else:\n", + " print(f'Sorry! The words \"{word_a}\" and \"{word_b}\" are NOT anagrams.')\n", + " return False\n", + "\n", + "anagram_checker(\"Silent\", \"listen\")" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# For testing purposes, we will write our code in the function\n", "def anagram_checker(word_a, word_b):\n", - " # Your code here\n", + " word_a_fold = word_a.casefold()\n", + " word_b_fold = word_b.casefold()\n", "\n", + " # Check lengths first because if not, these are not anagrams\n", + " if len(word_a_fold) != len(word_b_fold):\n", + " return False\n", + " # Compare sorted versions\n", + " if sorted(word_a_fold) == sorted(word_b_fold):\n", + " return True\n", + " else:\n", + " return False\n", + " \n", "# Run your code to check using the words below:\n", "anagram_checker(\"Silent\", \"listen\")" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 35, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "False" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "anagram_checker(\"Silent\", \"Night\")" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 36, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "anagram_checker(\"night\", \"Thing\")" ] @@ -97,12 +184,43 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 37, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ + "# This is the updated function for case sensitive anagrams. Here my approach changed in two places. \n", + "\n", + "# 1. I changed the variable naming in the function to word_a_str or word_a_string to denote which string I am comparing against\n", + "# 2. I incorporated is_case_sensitive first code block to ensure whether I will approach it with the fold case or leave it as is for case sensitive\n", + "\n", "def anagram_checker(word_a, word_b, is_case_sensitive):\n", - " # Modify your existing code here\n", + " # code block 1: check whether we are transforming the text to or not\n", + " if is_case_sensitive : \n", + " word_a_str = word_a\n", + " word_b_str = word_b\n", + " else:\n", + " word_a_str = word_a.casefold()\n", + " word_b_str = word_b.casefold()\n", + " # code block 2: Check for anagram\n", + " # Check lengths first because if not, these are not anagrams\n", + " if len(word_a_str) != len(word_b_str):\n", + " return False\n", + " # Compare sorted versions\n", + " if sorted(word_a_str) == sorted(word_b_str):\n", + " return True\n", + " else:\n", + " return False\n", "\n", "# Run your code to check using the words below:\n", "anagram_checker(\"Silent\", \"listen\", False) # True" @@ -110,9 +228,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 38, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "False" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "anagram_checker(\"Silent\", \"Listen\", True) # False" ] @@ -130,7 +259,7 @@ ], "metadata": { "kernelspec": { - "display_name": "new-learner", + "display_name": "dsi_participant", "language": "python", "name": "python3" }, @@ -144,7 +273,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.8" + "version": "3.9.18" } }, "nbformat": 4, From 403295d1fb5a00980a63cb20cee033214572dca4 Mon Sep 17 00:00:00 2001 From: Sykarim06 Date: Thu, 8 May 2025 20:38:45 -0400 Subject: [PATCH 2/4] Submitting Assignment 2 --- 02_activities/assignments/assignment_2.ipynb | 278 +++++++++++++++++-- 05_src/data/slides_data/provinces.txt | 1 + 2 files changed, 258 insertions(+), 21 deletions(-) create mode 100644 05_src/data/slides_data/provinces.txt diff --git a/02_activities/assignments/assignment_2.ipynb b/02_activities/assignments/assignment_2.ipynb index b98c21c65..c963677e6 100644 --- a/02_activities/assignments/assignment_2.ipynb +++ b/02_activities/assignments/assignment_2.ipynb @@ -73,10 +73,107 @@ { "cell_type": "code", "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'c:\\\\Users\\\\shafa'" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# importing os to change the directory to parent directory\n", + "\n", + "import os\n", + "\n", + "new_directory = \"c:\\\\Users\\\\shafa\\\\\" # changing the directory, if you run it on your machine - please change this to your preferred directory\n", + "\n", + "# Changing the directory\n", + "os.chdir(new_directory) \n", + "\n", + "# Confirm directory has changed\n", + "os.getcwd()" + ] + }, + { + "cell_type": "code", + "execution_count": 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'0,0,1,3,2,3,6,4,5,7,2,4,11,11,3,8,8,16,5,13,16,5,8,8,6,9,10,10,9,3,3,5,3,5,4,5,3,3,0,1\\n',\n", + " '0,1,1,2,2,5,1,7,4,2,5,5,4,6,6,4,16,11,14,16,14,14,8,17,4,14,13,7,6,3,7,7,5,6,3,4,2,2,1,1\\n',\n", + " '0,1,1,1,4,1,6,4,6,3,6,5,6,4,14,13,13,9,12,19,9,10,15,10,9,10,10,7,5,6,8,6,6,4,3,5,2,1,1,1\\n',\n", + " '0,0,0,1,4,5,6,3,8,7,9,10,8,6,5,12,15,5,10,5,8,13,18,17,14,9,13,4,10,11,10,8,8,6,5,5,2,0,2,0\\n',\n", + " '0,0,1,0,3,2,5,4,8,2,9,3,3,10,12,9,14,11,13,8,6,18,11,9,13,11,8,5,5,2,8,5,3,5,4,1,3,1,1,0\\n']\n" + ] + } + ], + "source": [ + "# using pprint to better explore the data visually\n", + "\n", + "from pprint import pprint\n", + "pprint(rows)" ] }, { @@ -128,6 +307,25 @@ "2. **Output Shape**: Ensure that the shape of your output data matches the number of patients, which is 60." ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Exploring the data first, also ensure the output shape is accurate\n", + "\n", + "import numpy as np\n", + "\n", + "file_path = all_paths[0]\n", + "\n", + "data = np.loadtxt(fname=file_path, delimiter=',') \n", + "\n", + "print(data)\n", + "print(type(data))\n", + "print(data.shape)\n", + "\n", + "del data # Now that we are done exploring, lets clear the numpy array if it was run in the step before." + ] + }, { "cell_type": "code", "execution_count": null, @@ -136,36 +334,52 @@ }, "outputs": [], "source": [ + "# Lets load numpy and get started. There was a mention of checking data quality with 60, so setting the variable to 60 first.\n", + "\n", + "no_of_patients = 60\n", + "\n", "import numpy as np\n", "\n", "def patient_summary(file_path, operation):\n", " data = np.loadtxt(fname=file_path, delimiter=',') # Load the data from the file\n", " ax = 1 # This specifies that the operation should be done for each row (patient)\n", - "\n", + " \n", + " # check for number of patients\n", + " if data.shape[0] != no_of_patients :\n", + " raise ValueError(\"Incorrect data loading, we don't have 60 records, please validate data loading again or check for change in raw file\")\n", " # Implement the specific operation based on the 'operation' argument\n", " if operation == 'mean':\n", - " # YOUR CODE HERE: Calculate the mean (average) number of flare-ups for each patient\n", - "\n", + " # YOUR CODE HERE: Calculate the mean (average) number of flare-ups for each patient\n", + " summary_values = np.mean(data, axis=ax)\n", " elif operation == 'max':\n", - " # YOUR CODE HERE: Calculate the maximum number of flare-ups experienced by each patient\n", - "\n", + " # YOUR CODE HERE: Calculate the maximum number of flare-ups experienced by each patient\n", + " summary_values = np.max(data, axis=ax)\n", " elif operation == 'min':\n", - " # YOUR CODE HERE: Calculate the minimum number of flare-ups experienced by each patient\n", - "\n", + " # YOUR CODE HERE: Calculate the minimum number of flare-ups experienced by each patient\n", + " summary_values = np.min(data, axis=ax)\n", " else:\n", - " # If the operation is not one of the expected values, raise an error\n", + " # If the operation is not one of the expected values, raise an error\n", " raise ValueError(\"Invalid operation. Please choose 'mean', 'max', or 'min'.\")\n", "\n", + "\n", " return summary_values" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 46, "metadata": { "id": "3TYo0-1SDLrd" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "60\n" + ] + } + ], "source": [ "# Test it out on the data file we read in and make sure the size is what we expect i.e., 60\n", "# Your output for the first file should be 60\n", @@ -205,7 +419,10 @@ { "cell_type": "markdown", "metadata": { - "id": "pb9EugDCJA4c" + "id": "pb9EugDCJA4c", + "vscode": { + "languageId": "raw" + } }, "source": [ "**Understanding the `check_zeros(x)` Helper Function**\n", @@ -228,7 +445,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 59, "metadata": { "id": "_svDiRkdIwiT" }, @@ -259,17 +476,35 @@ "source": [ "# Define your function `detect_problems` here\n", "\n", + "# My logical approach is to first complete the calculation of mean and then check for zero being present using the helper function provided.\n", + "# In the helper function, I pass on the mean_inflammations \n", + "\n", "def detect_problems(file_path):\n", " #YOUR CODE HERE: Use patient_summary() to get the means and check_zeros() to check for zeros in the means\n", - "\n", - " return" + " # Calculation: Get mean inflammation values for each patient\n", + " mean_inflammations = patient_summary(file_path, 'mean')\n", + " \n", + " # Data Quality Check: Use helper function to check for any mean that is equal to 0\n", + " zero_present = check_zeros(mean_inflammations)\n", + " \n", + " # Return the Result: will return true/false based on whether 0 is present\n", + " return zero_present\n", + " " ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 61, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "False\n" + ] + } + ], "source": [ "# Test out your code here\n", "# Your output for the first file should be False\n", @@ -314,7 +549,8 @@ "provenance": [] }, "kernelspec": { - "display_name": "Python 3", + "display_name": "dsi_participant", + "language": "python", "name": "python3" }, "language_info": { @@ -327,7 +563,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.8" + "version": "3.9.18" } }, "nbformat": 4, diff --git a/05_src/data/slides_data/provinces.txt b/05_src/data/slides_data/provinces.txt new file mode 100644 index 000000000..507cbd8b3 --- /dev/null +++ b/05_src/data/slides_data/provinces.txt @@ -0,0 +1 @@ +BCABMBSKONQCNLNBNSPE \ No newline at end of file From c879af86be4ef663f3dad006f317967913beb853 Mon Sep 17 00:00:00 2001 From: Sykarim06 Date: Wed, 14 May 2025 15:16:44 -0400 Subject: [PATCH 3/4] Revert assignment_1.ipynb to original version from the main branch --- 02_activities/assignments/assignment_1.ipynb | 157 ++----------------- 1 file changed, 14 insertions(+), 143 deletions(-) diff --git a/02_activities/assignments/assignment_1.ipynb b/02_activities/assignments/assignment_1.ipynb index 9277a3a88..bd82b6b8b 100644 --- a/02_activities/assignments/assignment_1.ipynb +++ b/02_activities/assignments/assignment_1.ipynb @@ -40,7 +40,7 @@ "source": [ "### Part 1: Building the base Anagram Checker\n", "\n", - "Given two valid strings, check to see if they are anagrams of each other. If it is, return `True`, else `False`. For this part, we can assume that case letters are the same as if it was a lowercase character.\n", + "Given two valid strings, check to see if they are anagrams of each other. If it is, return `True`, else `False`. For this part, we can assume that uppercase letters are the same as if it was a lowercase character.\n", "\n", "Examples of anagrams:\n", "* Silent and Listen\n", @@ -58,117 +58,30 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "True" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "\n", - "# In this example we don't care about the case sensitivity, hence we will convert all the text to lower casefold/caseless matching\n", - "\n", - "# Approach: I am thinking about folding, sorting the string, and then comparing strings. If these are really anagrams:\n", - "# Once sorted they should ideally be the same string representation\n", - "\n", - "# We should also handle for string length difference because in that situation, those are not really anagrams.\n", - "\n", - "def anagram_checker(word_a, word_b):\n", - " word_a_fold = word_a.casefold()\n", - " word_b_fold = word_b.casefold()\n", - "\n", - " # Check lengths first because if not, these are not anagrams\n", - " if len(word_a_fold) != len(word_b_fold):\n", - " print(f'Sorry! The words \"{word_a}\" and \"{word_b}\" are NOT anagrams — their lengths differ.')\n", - " return False\n", - " # Compare sorted versions\n", - " if sorted(word_a_fold) == sorted(word_b_fold):\n", - " print(f'Great job! The words \"{word_a}\" and \"{word_b}\" are anagrams.')\n", - " return True\n", - " else:\n", - " print(f'Sorry! The words \"{word_a}\" and \"{word_b}\" are NOT anagrams.')\n", - " return False\n", - "\n", - "anagram_checker(\"Silent\", \"listen\")" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "True" - ] - }, - "execution_count": 34, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "# For testing purposes, we will write our code in the function\n", "def anagram_checker(word_a, word_b):\n", - " word_a_fold = word_a.casefold()\n", - " word_b_fold = word_b.casefold()\n", + " # Your code here\n", "\n", - " # Check lengths first because if not, these are not anagrams\n", - " if len(word_a_fold) != len(word_b_fold):\n", - " return False\n", - " # Compare sorted versions\n", - " if sorted(word_a_fold) == sorted(word_b_fold):\n", - " return True\n", - " else:\n", - " return False\n", - " \n", "# Run your code to check using the words below:\n", "anagram_checker(\"Silent\", \"listen\")" ] }, { "cell_type": "code", - "execution_count": 35, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "False" - ] - }, - "execution_count": 35, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "anagram_checker(\"Silent\", \"Night\")" ] }, { "cell_type": "code", - "execution_count": 36, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "True" - ] - }, - "execution_count": 36, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "anagram_checker(\"night\", \"Thing\")" ] @@ -184,43 +97,12 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "True" - ] - }, - "execution_count": 37, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ - "# This is the updated function for case sensitive anagrams. Here my approach changed in two places. \n", - "\n", - "# 1. I changed the variable naming in the function to word_a_str or word_a_string to denote which string I am comparing against\n", - "# 2. I incorporated is_case_sensitive first code block to ensure whether I will approach it with the fold case or leave it as is for case sensitive\n", - "\n", "def anagram_checker(word_a, word_b, is_case_sensitive):\n", - " # code block 1: check whether we are transforming the text to or not\n", - " if is_case_sensitive : \n", - " word_a_str = word_a\n", - " word_b_str = word_b\n", - " else:\n", - " word_a_str = word_a.casefold()\n", - " word_b_str = word_b.casefold()\n", - " # code block 2: Check for anagram\n", - " # Check lengths first because if not, these are not anagrams\n", - " if len(word_a_str) != len(word_b_str):\n", - " return False\n", - " # Compare sorted versions\n", - " if sorted(word_a_str) == sorted(word_b_str):\n", - " return True\n", - " else:\n", - " return False\n", + " # Modify your existing code here\n", "\n", "# Run your code to check using the words below:\n", "anagram_checker(\"Silent\", \"listen\", False) # True" @@ -228,20 +110,9 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "False" - ] - }, - "execution_count": 38, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "anagram_checker(\"Silent\", \"Listen\", True) # False" ] @@ -259,7 +130,7 @@ ], "metadata": { "kernelspec": { - "display_name": "dsi_participant", + "display_name": "new-learner", "language": "python", "name": "python3" }, @@ -273,7 +144,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.18" + "version": "3.11.8" } }, "nbformat": 4, From e1b1efc0476ec9e5c42ef0b1a76417e2146c01da Mon Sep 17 00:00:00 2001 From: Sykarim06 Date: Wed, 14 May 2025 15:24:23 -0400 Subject: [PATCH 4/4] Implementing Requested Changes to Assignment-2 --- 02_activities/assignments/assignment_2.ipynb | 54 +++++--------------- 1 file changed, 12 insertions(+), 42 deletions(-) diff --git a/02_activities/assignments/assignment_2.ipynb b/02_activities/assignments/assignment_2.ipynb index c963677e6..647c746f9 100644 --- a/02_activities/assignments/assignment_2.ipynb +++ b/02_activities/assignments/assignment_2.ipynb @@ -73,36 +73,6 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'c:\\\\Users\\\\shafa'" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# importing os to change the directory to parent directory\n", - "\n", - "import os\n", - "\n", - "new_directory = \"c:\\\\Users\\\\shafa\\\\\" # changing the directory, if you run it on your machine - please change this to your preferred directory\n", - "\n", - "# Changing the directory\n", - "os.chdir(new_directory) \n", - "\n", - "# Confirm directory has changed\n", - "os.getcwd()" - ] - }, - { - "cell_type": "code", - "execution_count": 15, "metadata": { "id": "n0m48JsS-nMC" }, @@ -176,18 +146,18 @@ ], "source": [ "all_paths = [\n", - " \"python/05_src/data/assignment_2_data/inflammation_01.csv\",\n", - " \"python/05_src/data/assignment_2_data/inflammation_02.csv\",\n", - " \"python/05_src/data/assignment_2_data/inflammation_03.csv\",\n", - " \"python/05_src/data/assignment_2_data/inflammation_04.csv\",\n", - " \"python/05_src/data/assignment_2_data/inflammation_05.csv\",\n", - " \"python/05_src/data/assignment_2_data/inflammation_06.csv\",\n", - " \"python/05_src/data/assignment_2_data/inflammation_07.csv\",\n", - " \"python/05_src/data/assignment_2_data/inflammation_08.csv\",\n", - " \"python/05_src/data/assignment_2_data/inflammation_09.csv\",\n", - " \"python/05_src/data/assignment_2_data/inflammation_10.csv\",\n", - " \"python/05_src/data/assignment_2_data/inflammation_11.csv\",\n", - " \"python/05_src/data/assignment_2_data/inflammation_12.csv\"\n", + " \"../../05_src/data/assignment_2_data/inflammation_01.csv\",\n", + " \"../../05_src/data/assignment_2_data/inflammation_02.csv\",\n", + " \"../../05_src/data/assignment_2_data/inflammation_03.csv\",\n", + " \"../../05_src/data/assignment_2_data/inflammation_04.csv\",\n", + " \"../../05_src/data/assignment_2_data/inflammation_05.csv\",\n", + " \"../../05_src/data/assignment_2_data/inflammation_06.csv\",\n", + " \"../../05_src/data/assignment_2_data/inflammation_07.csv\",\n", + " \"../../05_src/data/assignment_2_data/inflammation_08.csv\",\n", + " \"../../05_src/data/assignment_2_data/inflammation_09.csv\",\n", + " \"../../05_src/data/assignment_2_data/inflammation_10.csv\",\n", + " \"../../05_src/data/assignment_2_data/inflammation_11.csv\",\n", + " \"../../05_src/data/assignment_2_data/inflammation_12.csv\"\n", "]\n", "\n", "with open(all_paths[0], 'r') as f:\n",