generated from mwc/project_argument
I am still plugging away at the argument project. I keep getting an
error message saying "pd is not defined", but I have defined it SO many times. Not sure what to do. I've put the ask into discord a few days ago, but have not received any feedback yet
This commit is contained in:
Heather
@@ -59,7 +59,7 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"#I chose this question becuase I generally try to eat healthy. Sometimes quick meals are a necesity. I am curious if common fast food restaurants truly offer healthier options "
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"#I chose this question because I generally try to eat healthy. Sometimes quick meals are a necessity. I am curious if common fast food restaurants truly offer healthier options "
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]
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},
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{
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@@ -72,7 +72,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"execution_count": 2,
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"id": "technical-evans",
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"metadata": {},
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"outputs": [],
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@@ -87,7 +87,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"execution_count": 2,
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"id": "overhead-sigma",
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"metadata": {},
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"outputs": [],
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@@ -96,25 +96,20 @@
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"\n",
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"# Load the dataset\n",
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"def pandas(pd):\n",
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" file_path = 'Fast_Food_Dataset/nutrition.csv' # Update this with the correct path\n",
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" data = pd.read_csv(file_path)"
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" file_path = pd.read_csv(\"Fast_Food_Dataset/nutrition.csv\") \n",
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"\n",
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" \n",
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"\n",
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" # Update this with the correct path\n",
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" "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"execution_count": 3,
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"id": "heated-blade",
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"metadata": {},
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"outputs": [
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{
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"ename": "SyntaxError",
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"evalue": "invalid syntax (1804757086.py, line 1)",
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"output_type": "error",
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"traceback": [
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"\u001b[0;36m Cell \u001b[0;32mIn[12], line 1\u001b[0;36m\u001b[0m\n\u001b[0;31m def data (pd.read_csv):\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
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]
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}
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],
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"outputs": [],
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"source": [
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"#check first 15 rows\n",
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"def data (read_csv):\n",
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@@ -141,12 +136,21 @@
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 4,
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"id": "basic-canadian",
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"metadata": {},
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"outputs": [],
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"source": [
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"#Import any helper files you need here\n"
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"#Import any helper files you need here\n",
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"\n",
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"import numpy as np\n",
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"import matplotlib as mpl\n",
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"import matplotlib.artist as martist\n",
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"import matplotlib.patches as mpatches\n",
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"import warnings\n",
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"warnings.filterwarnings(\"ignore\")\n",
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"\n",
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"\n"
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]
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},
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{
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@@ -173,12 +177,12 @@
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "44d5cdff-d651-46b8-8ee9-6bd6019c96c8",
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"execution_count": 1,
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"id": "0e3d2271-0361-4d42-a237-eff6b909c7b3",
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"metadata": {},
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"outputs": [],
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"source": [
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"I will use rows 1-15 \n"
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"#I will focus on rows 1-15 to reorganize the data into how many calories come from fat, which has the least amout of sodium and least amout of calories"
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]
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},
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{
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@@ -191,26 +195,14 @@
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": 11,
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"id": "negative-highlight",
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"metadata": {},
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"outputs": [
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{
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"ename": "NameError",
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"evalue": "name 'data' is not defined",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
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"Cell \u001b[0;32mIn[2], line 3\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;66;03m#######################################################################\u001b[39;00m\n\u001b[1;32m 2\u001b[0m \u001b[38;5;66;03m#import rows 1-15\u001b[39;00m\n\u001b[0;32m----> 3\u001b[0m \u001b[43mdata\u001b[49m\u001b[38;5;241m.\u001b[39mhead()\n\u001b[1;32m 4\u001b[0m \u001b[38;5;66;03m### \u001b[39;00m\n\u001b[1;32m 5\u001b[0m \u001b[38;5;66;03m### Your data analysis may include a statistic and/or a data visualization\u001b[39;00m\n\u001b[1;32m 6\u001b[0m \u001b[38;5;66;03m#######################################################################\u001b[39;00m\n",
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"\u001b[0;31mNameError\u001b[0m: name 'data' is not defined"
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]
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}
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],
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"outputs": [],
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"source": [
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"#######################################################################\n",
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"#import rows 1-15\n",
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"data.head()\n",
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"def file_path():\n",
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" file_path = pd.read_csv(\"Fast_Food_Dataset/nutrition.csv\") \n",
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"### \n",
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"### Your data analysis may include a statistic and/or a data visualization\n",
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"#######################################################################"
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@@ -218,12 +210,24 @@
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"execution_count": 14,
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"id": "victorian-burning",
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"metadata": {},
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"outputs": [],
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"outputs": [
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{
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"ename": "NameError",
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"evalue": "name 'pd' is not defined",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
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"Cell \u001b[0;32mIn[14], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m file_path \u001b[38;5;241m=\u001b[39m \u001b[43mpd\u001b[49m\u001b[38;5;241m.\u001b[39mread_csv(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFast_Food_Dataset/nutrition.csv\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
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"\u001b[0;31mNameError\u001b[0m: name 'pd' is not defined"
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]
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}
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],
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"source": [
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"# 💻 YOU CAN ADD NEW CELLS WITH THE \"+\" BUTTON "
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"file_path = pd.read_csv(\"Fast_Food_Dataset/nutrition.csv\")"
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]
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},
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{
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@@ -59,7 +59,7 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"#I chose this question becuase I generally try to eat healthy. Sometimes quick meals are a necesity. I am curious if common fast food restaurants truly offer healthier options "
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"#I chose this question because I generally try to eat healthy. Sometimes quick meals are a necessity. I am curious if common fast food restaurants truly offer healthier options "
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]
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},
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{
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@@ -72,7 +72,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"execution_count": 2,
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"id": "technical-evans",
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"metadata": {},
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"outputs": [],
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@@ -87,7 +87,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"execution_count": 2,
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"id": "overhead-sigma",
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"metadata": {},
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"outputs": [],
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@@ -96,13 +96,17 @@
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"\n",
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"# Load the dataset\n",
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"def pandas(pd):\n",
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" file_path = 'Fast_Food_Dataset/nutrition.csv' # Update this with the correct path\n",
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" data = pd.read_csv(file_path)"
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" file_path = pd.read_csv(\"Fast_Food_Dataset/nutrition.csv\") \n",
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"\n",
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" \n",
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"\n",
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" # Update this with the correct path\n",
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" "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"execution_count": 3,
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"id": "heated-blade",
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"metadata": {},
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"outputs": [],
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@@ -132,12 +136,21 @@
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"execution_count": 4,
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"id": "basic-canadian",
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"metadata": {},
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"outputs": [],
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"source": [
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"#Import any helper files you need here\n"
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"#Import any helper files you need here\n",
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"\n",
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"import numpy as np\n",
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"import matplotlib as mpl\n",
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"import matplotlib.artist as martist\n",
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"import matplotlib.patches as mpatches\n",
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"import warnings\n",
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"warnings.filterwarnings(\"ignore\")\n",
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"\n",
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"\n"
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]
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},
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{
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@@ -164,29 +177,12 @@
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 1,
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"id": "0e3d2271-0361-4d42-a237-eff6b909c7b3",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"id": "44d5cdff-d651-46b8-8ee9-6bd6019c96c8",
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"metadata": {},
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"outputs": [
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{
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"ename": "SyntaxError",
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"evalue": "invalid syntax (339389244.py, line 1)",
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"output_type": "error",
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"traceback": [
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"\u001b[0;36m Cell \u001b[0;32mIn[16], line 1\u001b[0;36m\u001b[0m\n\u001b[0;31m I will use rows 1-15\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
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]
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}
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],
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"source": [
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"I will use rows 1-15 \n"
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"#I will focus on rows 1-15 to reorganize the data into how many calories come from fat, which has the least amout of sodium and least amout of calories"
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]
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},
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{
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@@ -199,25 +195,14 @@
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": 11,
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"id": "negative-highlight",
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"metadata": {},
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"outputs": [
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{
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"ename": "NameError",
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"evalue": "name 'data' is not defined",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
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"Cell \u001b[0;32mIn[2], line 3\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;66;03m#######################################################################\u001b[39;00m\n\u001b[1;32m 2\u001b[0m \u001b[38;5;66;03m#import rows 1-15\u001b[39;00m\n\u001b[0;32m----> 3\u001b[0m \u001b[43mdata\u001b[49m\u001b[38;5;241m.\u001b[39mhead()\n\u001b[1;32m 4\u001b[0m \u001b[38;5;66;03m### \u001b[39;00m\n\u001b[1;32m 5\u001b[0m \u001b[38;5;66;03m### Your data analysis may include a statistic and/or a data visualization\u001b[39;00m\n\u001b[1;32m 6\u001b[0m \u001b[38;5;66;03m#######################################################################\u001b[39;00m\n",
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"\u001b[0;31mNameError\u001b[0m: name 'data' is not defined"
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]
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}
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],
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"outputs": [],
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"source": [
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"#######################################################################\n",
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"\n",
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"def file_path():\n",
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" file_path = pd.read_csv(\"Fast_Food_Dataset/nutrition.csv\") \n",
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"### \n",
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"### Your data analysis may include a statistic and/or a data visualization\n",
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"#######################################################################"
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@@ -225,12 +210,24 @@
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"execution_count": 14,
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"id": "victorian-burning",
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"metadata": {},
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"outputs": [],
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"outputs": [
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{
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"ename": "NameError",
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"evalue": "name 'pd' is not defined",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
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"Cell \u001b[0;32mIn[14], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m file_path \u001b[38;5;241m=\u001b[39m \u001b[43mpd\u001b[49m\u001b[38;5;241m.\u001b[39mread_csv(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFast_Food_Dataset/nutrition.csv\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
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"\u001b[0;31mNameError\u001b[0m: name 'pd' is not defined"
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]
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}
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],
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"source": [
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"# 💻 YOU CAN ADD NEW CELLS WITH THE \"+\" BUTTON "
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"file_path = pd.read_csv(\"Fast_Food_Dataset/nutrition.csv\")"
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]
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},
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{
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6
data/.ipynb_checkpoints/Untitled-checkpoint.ipynb
Normal file
6
data/.ipynb_checkpoints/Untitled-checkpoint.ipynb
Normal file
@@ -0,0 +1,6 @@
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{
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"cells": [],
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"metadata": {},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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6
data/Untitled.ipynb
Normal file
6
data/Untitled.ipynb
Normal file
@@ -0,0 +1,6 @@
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{
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"cells": [],
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"metadata": {},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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Reference in New Issue
Block a user