I am using DataNitro in my spreadsheet. When I write the values to a cell. It automatically guesses if format looks like a date. This is obviously not always helpfull!
dt_str = "08/20/13"
Cell("A1").value = dt_str
# puts date type in that cell
I am not sure whether this behaviour is from Excel 2010 or from DataNitro side. As I am writing this i am getting more convinced that this is an Excel issue. Anybody with experience on this?
Done some more research and I almost conviced it is Excel Issue. Solutions when Entering data directly is starting the cell with a ' This is obviously? not possible if I come in from python.
This is an Excel issue, and putting a single quote at the beginning is correct. You can do that as long as you use double quotes to delimit the string:
Cell("A1").value = "'10/1/2013"
Related
I have a Pandas DataFrame that has sports records in it. All of them look like this: "1-2-0", "17-12-1", etc., for wins, losses and ties. When I export this the records come up in different date formats within Excel. Some will come up as "12-May", others as "9/5/2001", and others will come up as I want them to.
The DataFrame that I want to export is named 'x' and this is the command I'm currently using. I tried it without the date_format part and it gave the same response in Excel.
x.to_csv(r'C:\Users\B\Desktop\nba.csv', date_format = '%s')
Also tried using to_excel and I kept getting errors while trying to export. Any ideas? I was thinking I am doing the date_format part wrong, but don't know to transfer the string of text directly instead of it getting automatically switched to a string.
Thanks!
I don't think its a python issue, but Excel auto detecting dates in your data.
But, see below to convert your scores to strings.
Try this,
import pandas as pd
df = pd.DataFrame({"lakers" : ["10-0-1"],"celtics" : ["11-1-3"]})
print(df.head())
here is the dataframe with made up data.
lakers celtics
0 10-0-1 11-1-3
Convert to dataframe to string
df = df.astype(str)
and save the csv:
df.to_csv('nba.csv')
Opening in LibreOffice gives me to columns with scores (made up)
You might have a use Excel issue going on here. Inline with my comment below, you can change any column in Excel to lots of different formats. In this case I believe Excel is auto detecting date formatting, incorrectly. Select your columns of data, right click, select format and change to anything else, like 'General'.
I'm using to csv to save a datframe which looks like this:
PredictionIdx CustomerInterest
0 fe789a06f3 0.654059
1 6238f6b829 0.654269
2 b0e1883ce5 0.666289
3 85e07cdd04 0.664172
in which I've a value '0e15826235' in first column.I'm writing this dataframe to csv using pandas to_csv() . But when I open this csv in google excel or libreoffice it shows 0E in excel and 0 in libreoffice. It is giving me problem during submission in kaggle. But one point to note here is that when I'm reading the same csv using pandas read_csv it shows the above value correctly in dataframe.
As noted in the first comment, the error is resulting from your choice of editor. Many editors will use some version of scientific notation that reads an e (in specific places like the second character) as an indicator of an exponent. Excel, for instance, will read it as a "base X raised to the power Y" where X are the numbers before the e and Y are the numbers after the e. This is a brief description of Excel's scientific notation.
This does not happen in the other cell entries because there appear to be other string-like characters. Excel, Libre, and possibly Google attempt to interpret what the entry is, rather than taking it literally.
In your question you write '0e15826235' with single quotes, indicating that it might be a string, but this might be something to make sure of when writing out the values to a file -- Excel and the rest might not know this is meant to be a string literal.
In general, check for the format of the value and consider what your eventual editor might "think" it is when it opens. For Excel specifically, a single quote character at the start of the string will force Excel to read it as a string. See this answer.
For me code below works correctly with google spreadsheets:
import pandas as pd
df = pd.DataFrame({'PredictionIdx': ['fe789a06f3',
'6238f6b829',
'b0e1883ce5',
'85e07cdd04'],
'CustomerInterest': [0.654059,
0.654269,
0.666289,
0.664172]})
df.to_csv('./test.csv', index = None)
Also csv is very simple text format, it doesn't hold any information about data types.
So you could use df.to_excel() as Nihal suggested, or adjust column type settings in your favourite spreadsheets viewer.
I am trying to create a csv using the python csv.dictwriter and open it with Excel 2013 so that everything is a string (left justified by default) and leave it in the *.csv format in Excel, too.
To get strings everywhere I use the QUOTE_ALL feature. To connect with Excel, I use the default Excel dialect. However, I get a name error when I put a string starting with a + sign into a cell, and any fields that are numeric (within the quotes). I can get rid of the name error by inserting a blank before the plus sign, but I really do not want the blank there.
I think that the way to get Excel to accept all this is to pass the strings with a leading equals sign before the opening double quote, ie:
="Field 1",="2",="+Third Field Here", ...
Is there any way to get the python libraries (latest 3.61 release) to accomplish something like this? I like the idea of a bulletproof library instead of rolling my own, as I have no control over what shows up within my data fields, but is this a covered use case for the standard library?
I have a Python 3 script that is loading some data into an Excel file on a Windows machine. I need the cell not just the number to be formatted as Currency.
I can use the following format to set the Number format for a cell:
sheet['D48'].number_format = '#,##0'
However, when I try a similar approach using the number format for Currency:
sheet['M48'].number_format = '($#,##0.00_);[Red]($#,##0.00)'
I get this for the custom format. Notice the extra backslashes, they are being added to the format so it does not match with the pre-defined Currency style.
(\$#,##0.00_);[Red](\$#,##0.00)
I have seen this question and used it to get this far. However the answer does not solve the extra backslash issue I am seeing.
Set openpyxl cell format to currency
I just formatted before placing into the cell.
"${:10,.2f}".format(7622086.82)
'$7,622,086.82'
I formatted the cell in Excel, and then copied the format.
This worked for me
.number_format = '[$$-409]#,##0.00;[RED]-[$$-409]#,##0.00'
I have a list of times in h:m format in an Excel spreadsheet, and I'm trying to do some manipulation with DataNitro but it doesn't seem to like the way Excel formats times.
For example, in Excel the time 8:32 is actually just the decimal number .355556 formatted to appear as 8:32. When I access that time with DataNitro it sees it as the decimal, not the string 8:32. If I change the format in Excel from Time to General or Number, it converts it to the decimal (which I don't want). The only thing I've found that works is manually going through each cell and placing ' in front of each one, then going through and changing the format type to General.
Is there any way to convert these times in Excel into strings so I can extract the info with DataNitro (which is only viewing it as a decimal)?
If .355556 (represented as 8:32) is in A1 then =HOUR(A1)&":"&MINUTE(A1) and Copy/Paste Special Values should get you to a string.
Ideally it seems that you probably don't want to change the way that excel keeps the data (Obviously depending on your use case).
If that is the case there is excellent post How do I read a date in Excel format in Python? that explains how to convert the float to a python date time object. Specifically the script by #John Machin works great.
import datetime
def minimalist_xldate_as_datetime(xldate, datemode):
# datemode: 0 for 1900-based, 1 for 1904-based
return (
datetime.datetime(1899, 12, 30)
+ datetime.timedelta(days=xldate + 1462 * datemode)
)
Note his disclaimer "Here's the bare-knuckle no-seat-belts use-at-own-risk version:" I have used it with no problems.