I am working on an excel file and the pandas shows the excel file like this.
How do i get rid of all Unnamed rows ?
This will do the trick
remove_cols = [col for col in gd.columns if 'Unnamed' in col]
gd.drop(remove_cols, axis='columns', inplace=True)
Looking at the result you are getting, the Excel data doesn't start on the first row. It also starts in column B instead of column A.
If you are able to edit the Excel file, I would recommend starting your data at A1 (by removing the empty column A and the empty rows at the top using Excel), as that will make later processing much easier for everyone reading the file.
If this file is not editable (perhaps it is generated by another party), you will need to skip the first couple of rows to read the correct headings:
gd = pd.read_excel(r"D:\gdp.xlsx", skiprows=3, usecols="B:L")
Related
I am trying to read an excel file and write every fourth row into a new Excel file. I'm using Pandas to read and write, and if int(num%4) == 0 to determine which rows to select, but the iteration and subsequent writing continue to escape me. I've tried my best to look up answers, but I'm a new programmer and struggling :/
If you're using Pandas I'm assuming you've loaded the data into a dataframe?
If so then consider this:
import pandas as pd
df = pd.read_csv('YourFile.csv')
df.iloc[::4]
#once you're done with the data you can save it to another csv file
df.to_csv('OutputFile.csv')
This will leave your dataframe df with the 4th, 8th, 12th, etc. rows from your original dataframe/file. You can then read/write to each row left in the dataframe df. To visualize the before and after just insert df.head() before and after the df.iloc[::4] expression.
I did not understand what the problem is to be more specific, but you should try pandas' iloc property (or even loc depending on your df), check more info in here: https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.iloc.html
I'm new to this page. I've managed to find myself in a little bit of an issue. Using python I'm looking for a way to loop through the different cells of an excel column using pandas and dataframes. The code I'm using is:
variable = pd.DataFrame(data, columns=['Column'])
for cell in variable:
print(cell)
And this only prints the first cell.
What am I doing wrong?
Not exactly sure what you are trying to do but here is a way to remove duplicate entries of the same text within a column in a dataframe.
df = df[df.column_name.apply(lambda x: x != 'Player')]
This loops through the whole column in the dataframe and ofcourse you can update the code to the action you want after the colon.
I'm new to python and just trying to redo my first project from matlab. I've written a code in vscode to import an excel file using pandas
filename=r'C:\Users\user\Desktop\data.xlsx'
sheet=['data']
with pd.ExcelFile(filename) as xls:
Dateee=pd.read_excel(xls, sheet,index_col=0)
Then I want to access data in a row and column.
I tried to print data using code below:
for key in dateee.keys():
print(dateee.keys())
but this returns nothing.
Is there anyway to access the data (as a list)?
You can iterate on each column, making the contents of each a list:
for c in df:
print(df[c].to_list())
df is what the dataframe was assigned as. (OP had inconsistent syntax & so I didn't use that.)
Look into df.iterrows() or df.itertuples() if you want to iterate by row. Example:
for row in df.itertuples():
print(row)
Look into df.iloc and df.loc for row and column selection of individual values, see Pandas iloc and loc – quickly select rows and columns in DataFrames.
Or df.iat or df.at for getting or setting single values, see here, here, and here.
When I create the Pandas dataframe, it detects the empty line at the top of the excel file as the column name and shows it as unnamed. But my column names should be the concentration names on the bottom line of it. How can I do this in a pandas? (Editing in Excel is a solution, but I want to automatically edit multiple excel files with python)
I think the column over there is not representing any column it is simply indication that there are many number of columns there. If it is a column and u don't want it u can simply drop it
df.drop("...")
if still it is still not resolved do comment.
I know how to read the whole dataset, I know how to read a part of it, but it always reads all of the columns from my excel file. I do it like this:
myfile = pd.ExcelFile('my_file.xlsx')
myfile.parse(2, skiprows=14, skipfooter= 2).dropna(axis=1, how='all')
But I can not read only one specific cell this way, because it read the whole row. Is there a way to limit the parser to one column?
UPDATE:
looking for a Pandas solution
Update your pandas to 0.24.2:
Docs: read_excel, specifically read usecols
I believe you will need to use a combination of skiprows and skipfooter to narrow down to specific row and usecols to get the column. This way you will get the specific cells value.