Reading and Passing Excel Filename with Pandas
2
I want to read excel file with Pandas, delete the header row and the first column and write the resultant data in an excel file with the same name. I want to do it for all the excel files in a folder. I have written the code for data reading and writing but having trouble with saving the data in a file with the same name. The code I have written is like this-
import numpy as np
import pandas as pd
import os
for filename in os.listdir ('./'):
if filename.endswith ('.xlsx'):
df = pd.read_excel ('new.xlsx', skiprows=1)
df.drop (df.columns [0], axis=1, inplace=True)
df.to_csv ('new.csv', index=False)
How can I automate my code for all the excel files in the same folder?
python excel pandas
asked Jan 3 at 14:42
Soelem Aafnan YehamSoelem Aafnan Yeham
112
add a comment |
2
I want to read excel file with Pandas, delete the header row and the first column and write the resultant data in an excel file with the same name. I want to do it for all the excel files in a folder. I have written the code for data reading and writing but having trouble with saving the data in a file with the same name. The code I have written is like this-
import numpy as np
import pandas as pd
import os
for filename in os.listdir ('./'):
if filename.endswith ('.xlsx'):
df = pd.read_excel ('new.xlsx', skiprows=1)
df.drop (df.columns [0], axis=1, inplace=True)
df.to_csv ('new.csv', index=False)
How can I automate my code for all the excel files in the same folder?
python excel pandas
asked Jan 3 at 14:42
Soelem Aafnan YehamSoelem Aafnan Yeham
112
add a comment |
2
2
2
I want to read excel file with Pandas, delete the header row and the first column and write the resultant data in an excel file with the same name. I want to do it for all the excel files in a folder. I have written the code for data reading and writing but having trouble with saving the data in a file with the same name. The code I have written is like this-
import numpy as np
import pandas as pd
import os
for filename in os.listdir ('./'):
if filename.endswith ('.xlsx'):
df = pd.read_excel ('new.xlsx', skiprows=1)
df.drop (df.columns [0], axis=1, inplace=True)
df.to_csv ('new.csv', index=False)
How can I automate my code for all the excel files in the same folder?
python excel pandas
asked Jan 3 at 14:42
Soelem Aafnan YehamSoelem Aafnan Yeham
112
I want to read excel file with Pandas, delete the header row and the first column and write the resultant data in an excel file with the same name. I want to do it for all the excel files in a folder. I have written the code for data reading and writing but having trouble with saving the data in a file with the same name. The code I have written is like this-
import numpy as np
import pandas as pd
import os
for filename in os.listdir ('./'):
if filename.endswith ('.xlsx'):
df = pd.read_excel ('new.xlsx', skiprows=1)
df.drop (df.columns [0], axis=1, inplace=True)
df.to_csv ('new.csv', index=False)
How can I automate my code for all the excel files in the same folder?
python excel pandas
python excel pandas
asked Jan 3 at 14:42
Soelem Aafnan YehamSoelem Aafnan Yeham
112
asked Jan 3 at 14:42
Soelem Aafnan YehamSoelem Aafnan Yeham
112
asked Jan 3 at 14:42
Soelem Aafnan YehamSoelem Aafnan Yeham
112
asked Jan 3 at 14:42
Soelem Aafnan YehamSoelem Aafnan Yeham
112
asked Jan 3 at 14:42
Soelem Aafnan YehamSoelem Aafnan Yeham
112
112
add a comment |
add a comment |
2 Answers
2
active
oldest
votes
2
Use variable filename in function read_excel and then create new file names by format and for remove first column is possible use DataFrame.iloc - select all columns without first:
for filename in os.listdir ('./'):
if filename.endswith ('.xlsx'):
df = pd.read_excel (filename, skiprows=1)
df.iloc[:, 1:].to_csv('new_{}.csv'.format(filename), index=False)
Another solution with glob, there is possible specify extensions:
import glob
for filename in glob.glob('./*.xlsx'):
df = pd.read_excel (filename, skiprows=1)
df.iloc[:, 1:].to_csv('new_{}.csv'.format(filename), index=False)
#python 3.6+
#df.iloc[:, 1:].to_csv (f'new_{filename}.csv', index=False)
answered Jan 3 at 14:45
jezraeljezrael
353k26317391
great ans as always, BTW by any chance do you know any doc where one can find out abbreviations likef''forformat,r''for regex, etc.
– meW
Jan 3 at 14:55
@meW - pure python is not easy for me, try ask it jpp :)
– jezrael
Jan 3 at 14:55
1
Okay will check with him.
– meW
Jan 3 at 14:56
Worked like a charm, thanks! Although, it is taking the whole name, including the .xlsx suffix, thus the name is being generated like new.xlsx.csv
– Soelem Aafnan Yeham
Jan 3 at 15:37
1
@Soelem Aafnan Yeham so add[:-5]likedf.iloc[:, 1:].to_csv('new_{}.csv'.format(filename[:-5]), index=False)for remove last 5 letters or usedf.iloc[:, 1:].to_csv('new_{}.csv'.format(os.path.splitext(filename)[0])), index=False)
– jezrael
Jan 3 at 16:22
add a comment |
0
Try Below for reading multiple files as follows:
import pandas as pd
import glob
# Read multiple files into one dataframe along with pandas `concat`
# if you have path defined like `/home/data/` then you can use `/home/data/*.xlsx` otherwise you directly mention the path.
df = pd.concat([pd.read_excel(files, sep=',', index=False, skiprows=1) for files in glob.glob("/home/data/*.xlsx")])
Alternative:
Read multiple files into one dataframe
all_Files = glob.glob('/home/data/*.xlsx')
df = pd.concat((pd.read_excel(files, sep=',', index=False, skiprows=1) for files in all_Files))
answered Jan 3 at 15:09
pygopygo
3,2211721
add a comment |
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2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
2
Use variable filename in function read_excel and then create new file names by format and for remove first column is possible use DataFrame.iloc - select all columns without first:
for filename in os.listdir ('./'):
if filename.endswith ('.xlsx'):
df = pd.read_excel (filename, skiprows=1)
df.iloc[:, 1:].to_csv('new_{}.csv'.format(filename), index=False)
Another solution with glob, there is possible specify extensions:
import glob
for filename in glob.glob('./*.xlsx'):
df = pd.read_excel (filename, skiprows=1)
df.iloc[:, 1:].to_csv('new_{}.csv'.format(filename), index=False)
#python 3.6+
#df.iloc[:, 1:].to_csv (f'new_{filename}.csv', index=False)
answered Jan 3 at 14:45
jezraeljezrael
353k26317391
great ans as always, BTW by any chance do you know any doc where one can find out abbreviations likef''forformat,r''for regex, etc.
– meW
Jan 3 at 14:55
@meW - pure python is not easy for me, try ask it jpp :)
– jezrael
Jan 3 at 14:55
1
Okay will check with him.
– meW
Jan 3 at 14:56
Worked like a charm, thanks! Although, it is taking the whole name, including the .xlsx suffix, thus the name is being generated like new.xlsx.csv
– Soelem Aafnan Yeham
Jan 3 at 15:37
1
@Soelem Aafnan Yeham so add[:-5]likedf.iloc[:, 1:].to_csv('new_{}.csv'.format(filename[:-5]), index=False)for remove last 5 letters or usedf.iloc[:, 1:].to_csv('new_{}.csv'.format(os.path.splitext(filename)[0])), index=False)
– jezrael
Jan 3 at 16:22
add a comment |
2
Use variable filename in function read_excel and then create new file names by format and for remove first column is possible use DataFrame.iloc - select all columns without first:
for filename in os.listdir ('./'):
if filename.endswith ('.xlsx'):
df = pd.read_excel (filename, skiprows=1)
df.iloc[:, 1:].to_csv('new_{}.csv'.format(filename), index=False)
Another solution with glob, there is possible specify extensions:
import glob
for filename in glob.glob('./*.xlsx'):
df = pd.read_excel (filename, skiprows=1)
df.iloc[:, 1:].to_csv('new_{}.csv'.format(filename), index=False)
#python 3.6+
#df.iloc[:, 1:].to_csv (f'new_{filename}.csv', index=False)
answered Jan 3 at 14:45
jezraeljezrael
353k26317391
great ans as always, BTW by any chance do you know any doc where one can find out abbreviations likef''forformat,r''for regex, etc.
– meW
Jan 3 at 14:55
@meW - pure python is not easy for me, try ask it jpp :)
– jezrael
Jan 3 at 14:55
1
Okay will check with him.
– meW
Jan 3 at 14:56
Worked like a charm, thanks! Although, it is taking the whole name, including the .xlsx suffix, thus the name is being generated like new.xlsx.csv
– Soelem Aafnan Yeham
Jan 3 at 15:37
1
@Soelem Aafnan Yeham so add[:-5]likedf.iloc[:, 1:].to_csv('new_{}.csv'.format(filename[:-5]), index=False)for remove last 5 letters or usedf.iloc[:, 1:].to_csv('new_{}.csv'.format(os.path.splitext(filename)[0])), index=False)
– jezrael
Jan 3 at 16:22
add a comment |
2
2
2
Use variable filename in function read_excel and then create new file names by format and for remove first column is possible use DataFrame.iloc - select all columns without first:
for filename in os.listdir ('./'):
if filename.endswith ('.xlsx'):
df = pd.read_excel (filename, skiprows=1)
df.iloc[:, 1:].to_csv('new_{}.csv'.format(filename), index=False)
Another solution with glob, there is possible specify extensions:
import glob
for filename in glob.glob('./*.xlsx'):
df = pd.read_excel (filename, skiprows=1)
df.iloc[:, 1:].to_csv('new_{}.csv'.format(filename), index=False)
#python 3.6+
#df.iloc[:, 1:].to_csv (f'new_{filename}.csv', index=False)
answered Jan 3 at 14:45
jezraeljezrael
353k26317391
Use variable filename in function read_excel and then create new file names by format and for remove first column is possible use DataFrame.iloc - select all columns without first:
for filename in os.listdir ('./'):
if filename.endswith ('.xlsx'):
df = pd.read_excel (filename, skiprows=1)
df.iloc[:, 1:].to_csv('new_{}.csv'.format(filename), index=False)
Another solution with glob, there is possible specify extensions:
import glob
for filename in glob.glob('./*.xlsx'):
df = pd.read_excel (filename, skiprows=1)
df.iloc[:, 1:].to_csv('new_{}.csv'.format(filename), index=False)
#python 3.6+
#df.iloc[:, 1:].to_csv (f'new_{filename}.csv', index=False)
answered Jan 3 at 14:45
jezraeljezrael
353k26317391
edited Jan 3 at 14:56
answered Jan 3 at 14:45
jezraeljezrael
353k26317391
answered Jan 3 at 14:45
jezraeljezrael
353k26317391
answered Jan 3 at 14:45
jezraeljezrael
353k26317391
353k26317391
great ans as always, BTW by any chance do you know any doc where one can find out abbreviations likef''forformat,r''for regex, etc.
– meW
Jan 3 at 14:55
@meW - pure python is not easy for me, try ask it jpp :)
– jezrael
Jan 3 at 14:55
1
Okay will check with him.
– meW
Jan 3 at 14:56
Worked like a charm, thanks! Although, it is taking the whole name, including the .xlsx suffix, thus the name is being generated like new.xlsx.csv
– Soelem Aafnan Yeham
Jan 3 at 15:37
1
@Soelem Aafnan Yeham so add[:-5]likedf.iloc[:, 1:].to_csv('new_{}.csv'.format(filename[:-5]), index=False)for remove last 5 letters or usedf.iloc[:, 1:].to_csv('new_{}.csv'.format(os.path.splitext(filename)[0])), index=False)
– jezrael
Jan 3 at 16:22
add a comment |
great ans as always, BTW by any chance do you know any doc where one can find out abbreviations likef''forformat,r''for regex, etc.
– meW
Jan 3 at 14:55
@meW - pure python is not easy for me, try ask it jpp :)
– jezrael
Jan 3 at 14:55
1
Okay will check with him.
– meW
Jan 3 at 14:56
Worked like a charm, thanks! Although, it is taking the whole name, including the .xlsx suffix, thus the name is being generated like new.xlsx.csv
– Soelem Aafnan Yeham
Jan 3 at 15:37
1
@Soelem Aafnan Yeham so add[:-5]likedf.iloc[:, 1:].to_csv('new_{}.csv'.format(filename[:-5]), index=False)for remove last 5 letters or usedf.iloc[:, 1:].to_csv('new_{}.csv'.format(os.path.splitext(filename)[0])), index=False)
– jezrael
Jan 3 at 16:22
great ans as always, BTW by any chance do you know any doc where one can find out abbreviations like
f'' for format, r'' for regex, etc.– meW
Jan 3 at 14:55
great ans as always, BTW by any chance do you know any doc where one can find out abbreviations like
f'' for format, r'' for regex, etc.– meW
Jan 3 at 14:55
@meW - pure python is not easy for me, try ask it jpp :)
– jezrael
Jan 3 at 14:55
@meW - pure python is not easy for me, try ask it jpp :)
– jezrael
Jan 3 at 14:55
1
1
Okay will check with him.
– meW
Jan 3 at 14:56
Okay will check with him.
– meW
Jan 3 at 14:56
Worked like a charm, thanks! Although, it is taking the whole name, including the .xlsx suffix, thus the name is being generated like new.xlsx.csv
– Soelem Aafnan Yeham
Jan 3 at 15:37
Worked like a charm, thanks! Although, it is taking the whole name, including the .xlsx suffix, thus the name is being generated like new.xlsx.csv
– Soelem Aafnan Yeham
Jan 3 at 15:37
1
1
@Soelem Aafnan Yeham so add
[:-5] like df.iloc[:, 1:].to_csv('new_{}.csv'.format(filename[:-5]), index=False) for remove last 5 letters or use df.iloc[:, 1:].to_csv('new_{}.csv'.format(os.path.splitext(filename)[0])), index=False)– jezrael
Jan 3 at 16:22
@Soelem Aafnan Yeham so add
[:-5] like df.iloc[:, 1:].to_csv('new_{}.csv'.format(filename[:-5]), index=False) for remove last 5 letters or use df.iloc[:, 1:].to_csv('new_{}.csv'.format(os.path.splitext(filename)[0])), index=False)– jezrael
Jan 3 at 16:22
add a comment |
0
Try Below for reading multiple files as follows:
import pandas as pd
import glob
# Read multiple files into one dataframe along with pandas `concat`
# if you have path defined like `/home/data/` then you can use `/home/data/*.xlsx` otherwise you directly mention the path.
df = pd.concat([pd.read_excel(files, sep=',', index=False, skiprows=1) for files in glob.glob("/home/data/*.xlsx")])
Alternative:
Read multiple files into one dataframe
all_Files = glob.glob('/home/data/*.xlsx')
df = pd.concat((pd.read_excel(files, sep=',', index=False, skiprows=1) for files in all_Files))
answered Jan 3 at 15:09
pygopygo
3,2211721
add a comment |
0
Try Below for reading multiple files as follows:
import pandas as pd
import glob
# Read multiple files into one dataframe along with pandas `concat`
# if you have path defined like `/home/data/` then you can use `/home/data/*.xlsx` otherwise you directly mention the path.
df = pd.concat([pd.read_excel(files, sep=',', index=False, skiprows=1) for files in glob.glob("/home/data/*.xlsx")])
Alternative:
Read multiple files into one dataframe
all_Files = glob.glob('/home/data/*.xlsx')
df = pd.concat((pd.read_excel(files, sep=',', index=False, skiprows=1) for files in all_Files))
answered Jan 3 at 15:09
pygopygo
3,2211721
add a comment |
0
0
0
Try Below for reading multiple files as follows:
import pandas as pd
import glob
# Read multiple files into one dataframe along with pandas `concat`
# if you have path defined like `/home/data/` then you can use `/home/data/*.xlsx` otherwise you directly mention the path.
df = pd.concat([pd.read_excel(files, sep=',', index=False, skiprows=1) for files in glob.glob("/home/data/*.xlsx")])
Alternative:
Read multiple files into one dataframe
all_Files = glob.glob('/home/data/*.xlsx')
df = pd.concat((pd.read_excel(files, sep=',', index=False, skiprows=1) for files in all_Files))
answered Jan 3 at 15:09
pygopygo
3,2211721
Try Below for reading multiple files as follows:
import pandas as pd
import glob
# Read multiple files into one dataframe along with pandas `concat`
# if you have path defined like `/home/data/` then you can use `/home/data/*.xlsx` otherwise you directly mention the path.
df = pd.concat([pd.read_excel(files, sep=',', index=False, skiprows=1) for files in glob.glob("/home/data/*.xlsx")])
Alternative:
Read multiple files into one dataframe
all_Files = glob.glob('/home/data/*.xlsx')
df = pd.concat((pd.read_excel(files, sep=',', index=False, skiprows=1) for files in all_Files))
answered Jan 3 at 15:09
pygopygo
3,2211721
edited Jan 3 at 15:52
answered Jan 3 at 15:09
pygopygo
3,2211721
answered Jan 3 at 15:09
pygopygo
3,2211721
answered Jan 3 at 15:09
pygopygo
3,2211721
3,2211721
add a comment |
add a comment |
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