How to remove NaN values from csv file?-CodePudding

I have a csv file with the following data:

List Of Tables
DimCurrency
DimOrganization
DimProduct
DimProductCategory
DimProductSubcategory
DimPromotion

Now, I need to read this data and append it to a list.

But when I try to read the data using the following code

table_col = ['table']
df1 = pd.read_csv('E:/Tabledata.csv', delimiter=',', names=table_col, header=0)
print(df1)

I get the Output as:

                       table
DimCurrency              NaN
DimOrganization          NaN
DimProduct               NaN
DimProductCategory       NaN
DimProductSubcategory    NaN
DimPromotion             NaN

I tried to remove to NaN values using df.fillna('') method, it gave me the output:

                      table
DimCurrency
DimOrganization
DimProduct
DimProductCategory
DimProductSubcategory
DimPromotion

And when I try to append this to a list, it returns me:

['', '', '', '', '', '']

Any suggestions how can I resolve this?

CodePudding user response：

Use read_csv:

>>> pd.read_csv('E:/Tabledata.csv', squeeze=True).tolist()
['DimCurrency',
 'DimOrganization',
 'DimProduct',
 'DimProductCategory',
 'DimProductSubcategory',
 'DimPromotion']

Or you can simply use:

lines = [line.strip() for line in open('E:/Tabledata.csv').readlines()][1:]

CodePudding user response：

If your goal is simply to read a single column csv file into a list, don' use pandas but pure python:

with open('Tabledata.csv') as f:
    for i in range(1): # set here the number of header lines to skip
        next(f)
    out = list(map(str.strip, f.readlines()))

output:

['DimCurrency',
 'DimOrganization',
 'DimProduct',
 'DimProductCategory',
 'DimProductSubcategory',
 'DimPromotion']

CodePudding user response：

seems like the content you need is in index column so do this after import data into dataframe.

list(df1.index)

output:

['DimCurrency', 'DimOrganization', 'DimProduct', 'DimProductCategory', 'DimProductSubcategory', 'DimPromotion']