Hey guys I've looked around a lot with importing csv files using pandas however even though my file path is correct I get thrown tons of errors
import pandas as pd
df = pd.read_csv(r"C:\Users\Liam\PycharmProjects\assignment1\pipeline-incidents-comprehensive-data.csv")
print(df)
all errors as seen here
I am very new to python (1 week) so i do realize this is a very simple problem so any assistance is greatly appreciated
import pandas as pd
path = "C:\\Users\\Liam\\PycharmProjects\\assignment1\\pipeline-incidents-comprehensive-data.csv"
df = pd.read_csv()
print(df)
Related
I just want to import this csv file. It can read it but somehow it doesn't create columns. Does anyone know why?
This is my code:
import pandas as pd
songs_data = pd.read_csv('../datasets/spotify-top50.csv', encoding='latin-1')
songs_data.head(n=10)
Result that I see in Jupyter:
P.S.: I'm kinda new to Jupyter and programming, but after all I found it should work properly. I don't know why it doesn't do it.
To properly load a csv file you should specify some parameters. for example in you case you need to specify quotechar:
df = pd.read_csv('../datasets/spotify-top50.csv',quotechar='"',sep=',', encoding='latin-1')
df.head(10)
If you still have a problem you should have a look at your CSV file again and also pandas documentation, so that you can set parameters to match with your CSV file structure.
I am very new to pandas, so I wanted to convert this HTML table to CSV file with the pandas however my CSV file is giving me a weird sign and it didn't manage to covert all the table over to the CSV.
Here's my code. I read about using beautifulsoup but I'm not too sure how to use the function.
import as pandas
df = pd.read_html('https://aim-sg.caas.gov.sg/aip/2020-10-13/final/2020-09-10-Non-AIR'
'AC/html/eAIP/ENR-3.1-en-GB.html?s=B2EE1C5E1D2A684224A194E69D18338A560504FC#ENR-3.1')
df[0].to_csv('ENR3.0.csv')
Thank you!
Edited: I have changed my import to import pandas as dp but i still did not manage to convert all the HTML table to CSV file.
Greatly appreciate all your help!
You can use pandas itself to do this. You have messed up with the import statement. Here is how you do it correctly:
import pandas as pd
df = pd.read_html('https://aim-sg.caas.gov.sg/aip/2020-10-13/final/2020-09-10-Non-AIR'
'AC/html/eAIP/ENR-3.1-en-GB.html?s=B2EE1C5E1D2A684224A194E69D18338A560504FC#ENR-3.1')
df[0].to_csv('ENR3.0.csv', index = False)
If you want to get all the dataframes present within the variable df, then replace the last line with this:
for x in range(len(df)):
df[x].to_csv(f"CSV_File_{x+1}", index = False)
There is issue in import statement
It should be import pandas as pd and not import as pandas, as your are using alias pd in the code below.
Study about beautiful soup and use lxml parser to parse required data ( it is very fast ).
This link might help you out:
BeautifulSoup different parsers
If any other help is required, then do leave a comment on this post and will try to sort our your issue :)
Made correction in your code:
import pandas as pd
df = pd.read_html('https://aim-sg.caas.gov.sg/aip/2020-10-13/final/2020-09-10-Non-AIR'
'AC/html/eAIP/ENR-3.1-en-GB.html?s=B2EE1C5E1D2A684224A194E69D18338A560504FC#ENR-3.1')
df[0].to_csv('ENR3.0.csv')
I'm a new Python user and am simply trying to export an Excel (or CSV) file into Jupyter Notebook to play around with.
From google searching, the common code I see is something like the below:
import pandas as pd
from pandas import ExcelWriter
from pandas import ExcelFile
df = pd.read_excel('File.xlsx', sheetname='Sheet1')
print("Column headings:")
print(df.columns)
I tried this with a CSV file and got the below error message:
File "", line 5
df = pd.read_excel(C:\Users\dhauge1\Desktop\Python Workshop\fortune500.csv, sheetname=fortune500)
^ SyntaxError: invalid syntax
Please see above for error message. Is anyone able to help me understand what I'm doing wrong?
when reading a csv file use the comand pd.read_csv('filename')
This question already exists:
Reading CSV files in Python, using Jupyter Notebook through IntelliJ IDEA
Closed 4 years ago.
Im trying to tackle the Kaggle Titanic challenge. Bear with me, as Im fairly new to data science. I was previously struggling to get the following syntax to work: my previous question(Reading CSV files in Python 3.6, using IntelliJ IDEA)
Reading CSV files in Python, using Jupyter Notebook through IntelliJ IDEA
import numpy as np
import pandas as pd
from pandas import Series,Dataframe
titanic_df = pd.read_csv('train.csv')
titanic.head()
However, using the below code, I am able to open the file and read it/print its contents, but i need to convert the data to a dataframe so that it can be worked with. Any suggestions?
file_path = '/Volumes/LACIE SETUP/Data_Science/Data_Analysis_Viz_InPython/Example_Projects/train.csv'
with open(file_path) as train_fp:
for line in train_fp:
# print(line)
This above code was able to print out the data but when I tried passing
'file_path' to:
titanic_df = pd.read_csv('file_path.csv')
i received the same error as before. Not sure what Im doing wrong. I KNOW the file 'train.csv' exists in that location because 1) i put it there and 2) its contents can be printed when pointed to its location.
So what the heck am I doing wrong??? :/
read_csv will create a Pandas DataFrame. So, as long as your file path is right, this following code should work. Also, make sure to use the file_path variable and not the string "file_path.csv"
import pandas as pd
file_path = '/Volumes/LACIE SETUP/Data_Science/Data_Analysis_Viz_InPython/Example_Projects/train.csv'
titanic_df = pd.read_csv(file_path)
titanic_df.head()
I have large data-frame in a Csv file sample1 from that i have to generate a new Csv file contain only 100 data-frame.i have generate code for it.but i am getting key Error the label[100] is not in the index?
I have just tried as below,Any help would be appreciated
import pandas as pd
data_frame = pd.read_csv("C:/users/raju/sample1.csv")
data_frame1 = data_frame[:100]
data_frame.to_csv("C:/users/raju/sample.csv")`
`
The correct syntax is with iloc:
data_frame.iloc[:100]
A more efficient way to do it is to use nrows argument who purpose is exactly to extract portions of files. This way you avoid wasting resources and time parsing useless rows:
import pandas as pd
data_frame = pd.read_csv("C:/users/raju/sample1.csv", nrows=101) # 100+1 for header
data_frame.to_csv("C:/users/raju/sample.csv")