I am new to python and have looked at a number of similar problems on SO, but cannot find anything quite like the problem that I have and am therefore putting it forward:
I have an .xlsx dataset with data spread across eight worksheets and I want to do the following:
sum the values in the 14th column in each worksheet (the format, layout and type of data (scores) is the same in column 14 across all worksheets)
create a new worksheet with all summed values from column 14 in each worksheet
sort the totaled scores from highest to lowest
plot the summed values in a bar chart to compare
I cannot even begin this process because I am struggling at the first point. I am using pandas and am having trouble reading the data from one specific worksheet - I only seem to be able to read the data from the first worksheet only (I print the outcome to see what my system is reading in).
My first attempt produces an `Empty DataFrame':
import pandas as pd
y7data = pd.read_excel('Documents\\y7_20161128.xlsx', sheetname='7X', header=0,index_col=0,parse_cols="Achievement Points",convert_float=True)
print y7data
I also tried this but it only exported the entire first worksheet's data as opposed to the whole document (I am trying to do this so that I can understand how to export all data). I chose to do this thinking that maybe if I exported the data to a .csv, then it might give me a clearer view of what went wrong, but I am nonethewiser:
import pandas as pd
import numpy as np
y7data = pd.read_excel('Documents\\y7_20161128.xlsx')
y7data.to_csv("results.csv")
I have tried a number of different things to try and specify which column within each worksheet, but cannot get this to work; it only seems to produce the results for the first worksheet.
How can I, firstly, read the data from column 14 in every worksheet, and then carry out the rest of the steps?
Any guidance would be much appreciated.
UPDATE (for those using Enthought Canopy and struggling with openpyxl):
I am using Enthought Canopy IDE and was constantly receiving an error message around openpyxl not being installed no matter what I tried. For those of you having the same problem, save yourself lots of time and read this post. In short, register for an Enthought Canopy account (it's free), then run this code via the Canopy Command Prompt:
enpkg openpyxl 1.8.5
I think you can use this sample file:
First read all columns in each sheet to list of columns called y7data:
y7data = [pd.read_excel('y7_20161128.xlsx', sheetname=i, parse_cols=[13]) for i in range(3)]
print (y7data)
[ a
0 1
1 5
2 9, a
0 4
1 2
2 8, a
0 5
1 8
2 5]
Then concat all columns together, I add keys which are used for axis x in graph, sum all columns, remove second level of MultiIndex (a, a, a in sample data) by reset_index and last sort_values:
print (pd.concat(y7data, axis=1, keys=['a','b','c']))
a b c
a a a
0 1 4 5
1 5 2 8
2 9 8 5
summed = pd.concat(y7data, axis=1, keys=['a','b','c'])
.sum()
.reset_index(drop=True, level=1)
.sort_values(ascending=False)
print (summed)
c 18
a 15
b 14
dtype: int64
Create new DataFrame df, set column names and write to_excel:
df = summed.reset_index()#.
df.columns = ['a','summed']
print (df)
a summed
0 c 18
1 a 15
2 b 14
If need add new sheet use this solution:
from openpyxl import load_workbook
book = load_workbook('y7_20161128.xlsx')
writer = pd.ExcelWriter('y7_20161128.xlsx', engine='openpyxl')
writer.book = book
writer.sheets = dict((ws.title, ws) for ws in book.worksheets)
df.to_excel(writer, "Main", index=False)
writer.save()
Last Series.plot.bar:
import matplotlib.pyplot as plt
summed.plot.bar()
plt.show()
From what I understand, your immediate problem is managing to load the 14th column from each of your worksheets.
You could be using ExcelFile.parse instead of read_excel and loop over your sheets.
xls_file = pd.ExcelFile('Documents\\y7_20161128.xlsx')
worksheets = ['Sheet1', 'Sheet2', 'Sheet3']
series = [xls_file.parse(sheet, parse_cols=[13]) for sheet in worksheets]
df = pd.DataFrame(series)
And from that, sum() your columns and keep going.
Using ExcelFile and then ExcelFile.parse() has the advantage to load your Excel file only once, and iterate over each worksheet. Using read_excel makes your Excel file to be loaded in each iteration, which is useless.
Documentation for pandas.ExcelFile.parse.
Related
Coding in Python 2.7. I have a csv file already present called input.csv. In that file we have 3 headers — Filename, Category, Version — under which certain values already exist.
I want to know how I can reopen the csv file and input only one value multiple times under the "Version" column such that whatever was written under "Version" gets overwritten by the new input.
So suppose under the "Version" column I had 3 inputs in 3 rows:
VERSION
55
66
88
It gets rewritten by my new input 10 so it will look like:
VERSION
10
10
10
I know normally we input csv row-wise but this time around I just want to input column wise under that specific header "Version".
Solution 1:
With pandas, you can use:
import pandas as pd
df = pd.read_csv(file)
df['VERSION'] = 10
df.to_csv(file, index=False)
Solution 2: If there are multiple rows (and you only want first 3), then you can use:
df.loc[df.index < 3, ['VERSION']] = 10
instead of:
df['VERSION'] = 10
I've been trying to sort my spreadsheet by 4 columns. Using win32com, I have managed to sort by 3 columns using the below code:
excel = win32com.client.Dispatch("Excel.Application")
wb= excel.Workbooks.Open('.xlsx')
ws= wb.worksheets[0]
ws.Range(D6:D110).Sort(Key1=ws.Range('D1'), Order1=1, Key2=ws.Range('E1'), Order2=2, Key3=ws.Range('G1'), Order3=3, Orientation=1)
However, when I try to add Key4, it says Key4 is an unexpected keyword argument. Is the Range.Sort function limited to only 3 keys? Is there a way to add a 4th?
Is there maybe another way to do this using pandas or openpyxl?
Thanks in advance!
Try reading in the excel sheet then sorting by header names. This assumes that your excel sheet is formatted correctly like a CSV.
import pandas as pd
df = pd.read_excel('filename.xlsx')
df = df.sort_values(['key1','key2','key3','key4'], axis=1)
df.to_excel('filename2.xlsx')
Simply sort twice or however many times needed in series of three keys.
xlAscending = 1
xlSortColumns = 1
xlYes = 1
ws.Range(D6:D110).Sort(Key1=ws.Range('D1'), Order1=xlAscending,
Key2=ws.Range('E1'), Order2=xlAscending,
Key3=ws.Range('G1'), Order3=xlAscending,
header=xlYes, Orientation=xlSortColumns)
# FOURTH SORT KEY (ADJUST TO NEEDED COLUMN)
ws.Range(D6:D110).Sort(Key1=ws.Range('H1'), Order1=xlAscending,
header=xlYes, Orientation=xlSortColumns)
By the way your Order numbers should only be 1, 2, or -4135 per the xlSortOrder constants.
I have to read an Excel sheet in pandas which contains multiple sheets.
Unfortunately, the number of white space rows before the header starts seems to be different:
pd.read_excel('foo.xlsx', header=[2,3], sheet_name='first')
pd.read_excel('foo.xlsx', header=[1,2], sheet_name='second')
Is there an elegant way to fix this and read the Excel into a pandas.Dataframe with an additional column which contains the name of each sheet?
I.e. how can
pd.read_excel(file_name, sheet_name=None)
be passed a varying header argument or choose at least the 2 first (non empty) rows as header?
edit
dynamically skip top blank rows of excel in python pandas
seems to be related but not the solution as only the first headers are accepted.
edit2
Description of exact file structure:
... (varying number of empty rows)
__irrelevant_row__
HEADER_1
HEADER_2
where currently it is either 1 or 0 empty rows. But as pointed out in the comment it would be great if that would be more dynamic.
I am certain this could be done in a more neat fashion, but a way to achieve (I think) what you want is:
import openpyxl
import pandas as pd
book = openpyxl.load_workbook(PATH_TO_FILE)
for sh in book.sheetnames:
a = pd.DataFrame(book[sh].values).dropna(how='all').reset_index(drop=True)
a.columns = a.iloc[1]
a = a.iloc[2:]
a.iloc[0].index.name=sh
a["sheet"] = a.iloc[0].index.name
try:
b = b.append(a)
except NameError:
b = a.copy()
b.iloc[0].index.name = ''
print(b)
# header1 header2 sheet
#2 1 2 first
#3 3 4 first
#2 1 2 second
#3 3 4 second
#2 1 2 3rd
#3 3 4 3rd
Unfortunately I have no clue how it interacts with your actual data, but I do hope this helps you in your quest.
I'm building a program that collects data and adds it to an ongoing excel sheet weekly (read_excel() and concat() with the new data). The issue I'm having is that I need the columns to have the same name for presentation (it doesn't look great with x.1, x.2, ...).
I only need this on the final output. Is there any way to accomplish this? Would it be too time consuming to modify pandas?
you can create a list of custom headers that will be read into excel
newColNames = ['x','x','x'.....]
df.to_excel(path,header=newColNames)
You can add spaces to the end of the column name. It will appear the same in a Excel, but pandas can distinguish the difference.
import pandas as pd
df = pd.DataFrame([[1,2,3],[4,5,6],[7,8,9]], columns=['x','x ','x '])
df
x x x
0 1 2 3
1 4 5 6
2 7 8 9
I am writing a python code for beam sizing. I have an Excel workbook from AISC that has all the data of the shapes and other various information on the cross-sections. I would like to be able to reference data in particular cells in this Excel workbook in my python code.
For example if the width of rectangle is 2in and stored in cell A1 and the height is 10in and stored in cell B1 I want to write a code in python that somehow pulls in cell A1 and B1 and multiply them.
I do not need to export back into excel I just want to make python do all the work and use excel purely as reference material.
Thank you in advance for all your advice and input!!
Try pandas as well...might be easier to work with than lists in this case
DATA :
Width Height
4 2
4 4
1 1
4 5
Code
import pandas as pd
#read the file
beam = pd.read_csv('cross_section.csv')
beam['BeamSize'] = beam['Width']*beam['Height'] #do your calculations
Output:
>>> beam
Width Height BeamSize
0 4 2 8
1 4 4 16
2 1 1 1
3 4 5 20
4 2 2 4
You can slice and dice the data as you wish.
For eg, lets say you want the fifth beam :
>>> beam.ix[4]
Width 2
Height 2
BeamSize 4
Name: 4, dtype: int64
Check this for more info:
http://pandas.pydata.org/pandas-docs/stable/
You can read directly from excel as well..
Thank you for you inputs. I have found the solution I was looking for by using Numpy.
data = np.loadtxt('C:\Users[User_Name]\Desktop[fname].csv', delimiter=',')
using that it took the data and created an array with the data that I needed. Now I am able to use the data like any other matrix or array.
If you don't mind adding a (somewhat heavy) dependency to your project, pandas has a read_excel function that can read a sheet from an Excel workbook into a pandas DataFrame object, which acts sort of like a dictionary. Then reading a cell would just amount to something like:
data = pd.read_excel('/path/to/file.xls')
cell_a1 = data.loc[1, 'a'] # or however it organizes it on import
For future readers of this question, it should be mentioned that xlrd is the "most exact" solution to your requirements. It will allow you to read data directly from an Excel file (no need to convert to CSV first).
Many other packages that read Excel files (including pandas) use xlrd themselves to provide that capability. They are useful, but "heavier" than xlrd (larger, more dependencies, may require compilation of C code, etc.).
(Incidentally, pandas happens to use both xlrd and NumPy.)