I have an excel file composed of several sheets. I need to load them as separate dataframes individually. What would be a similar function as pd.read_csv("") for this kind of task?
P.S. due to the size I cannot copy and paste individual sheets in excel
Use pandas read_excel() method that accepts a sheet_name parameter:
import pandas as pd
df = pd.read_excel(excel_file_path, sheet_name="sheet_name")
Multiple data frames can be loaded by passing in a list. For a more in-depth explanation of how read_excel() works see: http://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_excel.html
If you can't type out each sheet name and want to read whole worksheet try this:
dfname=pd.ExcelFile('C://full_path.xlsx')
print(dfname.sheet_names)
df=pd.read_excel('C://fullpath.xlsx')
for items in dfname.sheet_names[1:]:
dfnew=pd.read_excel(full_path,sheet_name=items)
df=pd.concat([df,dfnew])
The thing is that pd.read_excel() can read the very first sheet and rest are unread.So you can use this
import pandas
# setting sheet_name = None, reads all sheets into a dict
sheets = pandas.read_excel(filepath, sheet_name=None)
# i will be the keys in a dictionary object
# the values are the dataframes of each sheet
for i in sheets:
print(f"sheet[{i}]")
print(f"sheet[{i}].columns={sheets[i].columns}")
for index, row in sheets[i].iterrows():
print(f"index={index} row={row}")
exFile = ExcelFile(f) #load file f
data = ExcelFile.parse(exFile) #this creates a dataframe out of the first sheet in file
Related
I am creating a class, where one of the methods "load()" wants to receive an excel file, retrieve the list of spreadsheets in the excel file and then return back the individual sheets of the file as a dictionary:
For example:
{“Sheet Name 1”: DataFrame,
“Sheet Name 2”: DataFrame,
“Sheet Name N”: DataFrame}
I am unsure of how best to do this. Other forums have suggested me to use xlrd or openpyxl but I have tried and can't solve this currently.
You can use openpyxl as follows
from openpyxl import load_workbook
workbook = load_workbook(filename="testing.xlsx")
# create the dictionary to hold the dataframes
data_dict = {}
# loop through each sheet, storing the sheetname and the dataframe
for sheet in workbook.sheetnames:
data_dict[sheet] = pd.read_excel('testing.xlsx', sheet_name=sheet)
I am accessing a series of Excel files in a for loop. I then read the data in the excel file to a pandas dataframe. I cant figure out how to append these dataframes together to then save the dataframe (now containing the data from all the files) as a new Excel file.
Here's what I tried:
for infile in glob.glob("*.xlsx"):
data = pandas.read_excel(infile)
appended_data = pandas.DataFrame.append(data) # requires at least two arguments
appended_data.to_excel("appended.xlsx")
Thanks!
Use pd.concat to merge a list of DataFrame into a single big DataFrame.
appended_data = []
for infile in glob.glob("*.xlsx"):
data = pandas.read_excel(infile)
# store DataFrame in list
appended_data.append(data)
# see pd.concat documentation for more info
appended_data = pd.concat(appended_data)
# write DataFrame to an excel sheet
appended_data.to_excel('appended.xlsx')
you can try this.
data_you_need=pd.DataFrame()
for infile in glob.glob("*.xlsx"):
data = pandas.read_excel(infile)
data_you_need=data_you_need.append(data,ignore_index=True)
I hope it can help.
DataFrame.append() and Series.append() have been deprecated and will be removed in a future version. Use pandas.concat() instead (GH35407).
I am using below code to read excel sheets from an excel file
df=pd.read_excel(ExcelFile,sheet_name="Sheet1")
What if i have 10 excel files with multiple tabs for example
Sheet1, Sheet2, Sheet3 and in some files
sheet names are in Capital for example "SHEET1", in this case how can i read those sheet names.
based on the pandas read_excel documentation you can give the sheet names as a list.
so you can give the sheet names like this:
sheet_names = ['sheet1','sheet2','sheet3']
df=pd.read_excel(ExcelFile,sheet_name=sheet_names)
if you give sheet_name = None It will read all the sheets.
you need sheet_name=None
dfs = pd.read_excel('filename.xlsx',sheet_name=None)
This will return a dictionary where key will be sheet_names and value will be dataframes.
you can see all the sheet names by,
dfs.keys()
to retrieve specific sheet data,
df = dfs['sheet_name']
I have one excel file with many rows of data. I have a second file with multiple sheets. Using python, I want to loop through each sheet on the second file, and merge it with the data on the first file (they have the same column headers).
As a final export, I would like to have all the merged data back on the first file.
I'm relatively new to python and don't have any code written except for reading in the pandas library and the two files.
Given that file1.xlsx is your main file and file2.xlsx is your file with the multiple sheets:
import pandas
df_main = pd.read_excel('file1.xlsx')
multiple_sheets = pd.read_excel('file2.xlsx', sheet_name=None) # None means all sheets, this produces a dict of DataFrames with the keys as the sheet names.
for x in multiple_sheets.values(): # Loop through dict with x as the df per sheet
# Cleanup before adding.
df_main = pd.concat([df_main, x], ignore_index=True)
From there, you can now do your cleanup and save the DataFrame as a new Excel file (i.e., df_main.to_excel('file1.xlsx')).
References:
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.concat.html
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_excel.html
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_excel.html
I am trying to read an excel sheet into df using pandas read_excel method. The excel file contains 6-7 different sheet. Out of it, 2-3 sheets are very huge. I only want to read one excel sheet out of the file.
If I copy the sheet out and read the time reduces by 90%.
I have read that xlrd that is used by pandas always loads the whole sheet to memory. I cannot change the format of the input.
Can you please suggest a way to improve the performance?
It's quite simple. Just do this.
import pandas as pd
xls = pd.ExcelFile('C:/users/path_to_your_excel_file/Analysis.xlsx')
df1 = pd.read_excel(xls, 'Sheet1')
print(df1)
# etc.
df2 = pd.read_excel(xls, 'Sheet2')
print(df2)
import pandas as pd
df = pd.read_excel('YourFile.xlsx', sheet_name = 'YourSheet_Name')
Whatever sheet you want to read just put the sheet name and your path to excel file.
Use openpyxl in read-only mode. See http://openpyxl.readthedocs.io/en/default/pandas.html