How do I skip rows in pandas while reading Excel?

How do you skip columns in pandas read?

Is it possible to skip some of the rows in the result from a pandas.

Read (eg. Readcsv)?
I know you can just do something like .drop(0, 1) but is there a way to use the indexing capabilities? >>> print df. 0 1 2 3 4. 0 1 1 1. 1 1 1 1. 2 1 1 1. 3 1 1 1. 4 1 1 1. 5 1 1 1. 6 1 1 1. 7 1 1 1. 8 1 1 1. 9 1 1 1. 10 1 1 1. 11 1 1 1. 12 1 1 1. 13 1 1 1. 14 1 1 1. 15 1 1 1. >>> df = pd.readcsv('df.txt', sep=',', skiprows=3)

This is an old question, but I found the answer after searching the web and posting this question in the pandas mailing list. The answer is

How do I exclude a column from pandas to Excel?

I have the following dataset, which I am using to perform data cleaning.

It has the columns 'datestart', 'dateend' and 'id', and I am using it as follows: import pandas as pd. Import numpy as np. Import datetime as dt. Start = pd.Timestamp('1/2017 0:0', tz='UTC') end = pd.Timestamp('1/10/2017 23:59', tz='UTC') df = pd.DataFrame(np.arange(4).ExcelWriter("data.xlsx")
df.toexcel(excel,'Sheet1') print("Save Success!"). I am successfully able to get everything into my Excel file except for the datestart column. I have used the dateutil module to change the format of the date in the datestart column from 'YYYY-MM-DD HH:MM:SS' to 'YYYY-MM-DDTTHH:MM:SS'. However, when I do the above, the value gets converted to 'NaN' and Excel does not recognise it as a date. Why is this happening?

You can't save NaNs.

How do I skip rows in pandas while reading Excel?

I'm reading data from an Excel file into a pandas DataFrame using: pd.

Readexcel('myfile.xlsx')
The Excel file has one of three possible formats: Data-type 1. Header-data. Data-type 2. Which is the "type" I'm dealing with. I only need to extract the header data and keep it in memory (as the rest is irrelevant to my analysis). The problem is, in Excel (Version: Excel 2010) there are blank rows where data are simply copied and pasted. So, I don't need to import any rows, but rather skip them.

I'm reading the first worksheet in the file, so there's no need to worry about the header row being in a different worksheet. I've tried to play around with the skiprows parameter for readexcel but have not been able to find a way to skip blank rows. Can anyone provide advice on how to do this? Thanks.
It sounds like you have a sheet with 2 columns: col1 col2. -----. And then you have one blank row that is just copied and pasted over the top. You could remove the blanks from your dataframe like this: import pandas as pd. Df = pd.readexcel('test.columns !