Pandas read_excel() parses date columns with blank values to NaT

Question

I am trying to read an excel file that has date columns with the below code

src1_df = pd.read_excel("src_file1.xlsx", keep_default_na = False)

Even though I have specified, keep_default_na = False, I see that the data frame has 'NaT' value(s) for corresponding blank cells in Excel date columns.

Please suggest, how to get a blank string instead of 'NaT' while parsing Excel files.

I am using Python 3.x and Pandas 0.23.4

Answer 1

src1_df = pd.read_excel("src_file1.xlsx", na_filter=False)

Then you will have empty string ("") as "na" value

In my case I read excel per line and replace "" and "NaT" to None:

for line in src1_df.values:
    for index, value in enumerate(line):
        if value == '' or isinstance(value, pd._libs.tslibs.nattype.NaTType):
            line[index] = None
dostuff_with(line)