I have a .csv file which looks as follows:link
I want to open this file using pandas and edit the column Coordinate by adding a constant value of 756 to each value in it. Finally, I want the changes to be reflected in the .csv file.
How do I do that?
Edit: What I had been doing is as follows (#EdChum):
df = pd.read_csv('C:/TestBook1.csv')
df = df[['Coordinate','Speed']]
Coord = df['Coordinate']
Coord = Coord + 756
This is where I was going wrong. From here it would have been a messy affair to save changes into the .csv file.
you can also type:
df["Coordinate"] = df["Coordinate"] + 756
#EdChum: Thanks for your comment. It kind of fired me up. I was unnecessarily complicating things for myself. Following is what I did:
df = pd.read_csv('C:/TestBook1.csv')
df = df[['Coordinate','Speed']]
df['Coordinate']+=756
df.to_csv('C:/TestBook1.csv')
Initially I was loading all the values of the column into a variable and trying to find a way to save it. After your comment I thought of experimenting and I am glad that it worked for me.
Define path where csv file is located
Location = r'C:\\'
df = pd.read_csv(Location,header=None)
df["Coorinate"].values +756
Do not forget to import pandas package
import pandas as pd
Related
Hi I am trying to create multiple csv files from a single big csv using python. The original csv file has multiple stocks data in 1 min date/time with Open, high, low, close, volume as other columns.
Sample data from original file is here
At first, I tried to copy individual Ticker and all its corresponding values to a new file with following code:
import pandas as pd
excel_file_path=r'C:\Users\mahan\Documents\test projects\01_07_APR_WEEKLY_expiry_data_VEGE_NF_AND_BNF_Options_Desktop_Vege.csv'
export_path=r"C:\Users\mahan\Documents\exportfiles\{output_file_name}_sheet.csv"
data= pd.read_csv(excel_file_path, index_col="Ticker") #Making data frame from csv file
rows= data.loc[['NIFTYWK17500CE']] #Retrieving rows by loc method
output_file_name ="NIFTYWK17500CE_"
print(type(rows))
rows
rows.to_csv(export_path)
Result was something like this:
a file was saved with the name "{output_file_name}__sheet.csv"
I failed at naming the file but data was copied pertaining to all the values with Ticker value 'NIFTYWK17500CE'.
Then I tried to create a array with column "Ticker" to find unique values. Created a dataframe with original file for all the data. And tried to use a For loop for values in the array matching the 1st column 'Ticker' and copy those data to a new file using the value in the exporting csv file name.
code as below:
import pandas as pd
excel_file_path=r'C:\Users\mahan\Documents\test projects\01_07_APR_WEEKLY_expiry_data_VEGE_NF_AND_BNF_Options_Desktop_Vege.csv'
df2=pd.read_csv(excel_file_path)
df2_uniques =df2['Ticker'].unique()
df2_counts=df2['Ticker'].value_counts()
for value in df2_uniques:
value=value.replace(' ', '_')
export_path=r"C:\Users\mahan\Documents\exportfiles\{value}__sheet.csv"
df=pd.read_csv(excel_file_path,index_col="Ticker")
rows=df.loc[['value']]
print(type(rows))
rows.to_csv(export_path)
Received an error:
KeyError: "None of [Index(['value'], dtype='object', name='Ticker')] are in the [index]"
Where did I went wrong:
In naming the file properly to save in earlier code.
In the second code.
Any help is really appreciated. Thanks in advance.
SOLVED
What worked for me was the following with comments:
import pandas as pd
excel_file_path=r'C:\Users\mahan\Documents\test projects\01_07_APR_WEEKLY_expiry_data_VEGE_NF_AND_BNF_Options_Desktop_Vege.csv'
df2=pd.read_csv(excel_file_path)
df2_uniques =df2['Ticker'].unique()
for value in df2_uniques:
value=value.replace(' ', '_')
df=pd.read_csv(excel_file_path,index_col="Ticker")
rows=df.loc[[value]] #Changed from 'value' to value
print(type(rows))
rows.to_csv(r'_'+value+'.csv')
#Removed export_path as filename and filepath together were giving me hard time to figure out.
#The files get saved in same filepath as the original imported filepath. So that'll do. sharing just for reference
Final output looks like this:
I can't know for sure without seeing the dataframe, but the error indicates that there is no column name 'Ticker'. It appears that you set this column to be the index, so you can try df2_uniques = set(df2.index).
changed
rows=df.loc[['value']]
to
rows=df.loc[[value]]
Also, Removed export_path as both filename and filepath together were giving me hard time to figure out.
The files get saved in same filepath as the original imported filepath. So that'll do. Sharing just for reference
Final code that worked looked like this:
import pandas as pd
excel_file_path=r'C:\Users\mahan\Documents\test projects\01_07_APR_WEEKLY_expiry_data_VEGE_NF_AND_BNF_Options_Desktop_Vege.csv'
df2=pd.read_csv(excel_file_path)
df2_uniques =df2['Ticker'].unique()
for value in df2_uniques:
value=value.replace(' ', '_')
df=pd.read_csv(excel_file_path,index_col="Ticker")
rows=df.loc[[value]] #Changed from 'value' to value
print(type(rows))
rows.to_csv(r'_'+value+'.csv')
I am trying to write a code that reads a csv file and can save each columns as a specific variable. I am having difficulty because the header is 7 lines long (something I can control but would like to just ignore if I can manipulate it in code), and then my data is full of important decimal places so it can not change to int( or maybe string?) I've also tried just saving each column by it's placement in the file but am struggling to run it. Any ideas?
Image shows my current code that I have slimmed to show important parts and circles data that prints in my console.
save each columns as a specific variable
import pandas as pd
pd.read_csv('file.csv')
x_col = df['X']
https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html
If what you are looking for is how to iterate through the columns, no matter how many there are. (Which is what I think you are asking.) Then this code should do the trick:
import pandas as pd
import csv
data = pd.read_csv('optitest.csv', skiprows=6)
for column in data.columns:
# You will need to define what this save() method is.
# Just placing it here as an example.
save(data[column])
The line about formatting your data as a number or a string was a little vague. But if it's decimal data, then you need to use float. See #9637665.
I have a CSV file, diseases_matrix_KNN.csv which has excel table.
Now, I would like to store all the numbers from the row like:
Hypothermia = [0,-1,0,0,0,0,0,0,0,0,0,0,0,0]
For some reason, I am unable to find a solution to this. Even though I have looked. Please let me know if I can read this type of data in the chosen form, using Python please.
most common way to work with excel is use Pandas.
Here is example:
import pandas as pd
df = pd.read_excel(filename)
print (df.iloc['Hypothermia']). # gives you such result
I am trying to restructure the way my precipitations' data is being organized in an excel file. To do this, I've written the following code:
import pandas as pd
df = pd.read_excel('El Jem_Souassi.xlsx', sheetname=None, header=None)
data=df["El Jem"]
T=[]
for column in range(1,56):
liste=data[column].tolist()
for row in range(1,len(liste)):
liste[row]=str(liste[row])
if liste[row]!='nan':
T.append(liste[row])
result=pd.DataFrame(T)
result
This code works fine and through Jupyter I can see that the result is good
screenshot
However, I am facing a problem when attempting to save this dataframe to a csv file.
result.to_csv("output.csv")
The resulting file contains the vertical index column and it seems I am unable to call for a specific cell.
(Hopefully, someone can help me with this problem)
Many thanks !!
It's all in the docs.
You are interested in skipping the index column, so do:
result.to_csv("output.csv", index=False)
If you also want to skip the header add:
result.to_csv("output.csv", index=False, header=False)
I don't know how your input data looks like (it is a good idea to make it available in your question). But note that currently you can obtain the same results just by doing:
import pandas as pd
df = pd.DataFrame([0]*16)
df.to_csv('results.csv', index=False, header=False)
Is there any way you can write value to specific place in given .csv file using pandas or csv module?
I have tried using csv_reader to read the file and find a line which fits my requirements though I couldn't figure out a way to switch value which is in the file to mine.
What I am trying to achieve here is that I have a spreadsheet of names and values. I am using JSON to update the values from the server and after that I want to update my spreadsheet also.
The latest solution which I came up with was to create separate sheet from which I will get updated data, but this one is not working, though there is no sequence in which the dict is written to the file.
def updateSheet(fileName, aValues):
with open(fileName+".csv") as workingSheet:
writer = csv.DictWriter(workingSheet,aValues.keys())
writer.writeheader()
writer.writerow(aValues)
I will appreciate any guidance and tips.
You can try this way to operate the specified csv file
import pandas as pd
a = ['one','two','three']
b = [1,2,3]
english_column = pd.Series(a, name='english')
number_column = pd.Series(b, name='number')
predictions = pd.concat([english_column, number_column], axis=1)
save = pd.DataFrame({'english':a,'number':b})
save.to_csv('b.csv',index=False,sep=',')