Strip whitespace from strings in a column

Question

I am using python csvkit to compare 2 files like this:

df1 = pd.read_csv('input1.csv', sep=',\s+', delimiter=',', encoding="utf-8")
df2 = pd.read_csv('input2.csv', sep=',\s,', delimiter=',', encoding="utf-8")
df3 = pd.merge(df1,df2, on='employee_id', how='right')
df3.to_csv('output.csv', encoding='utf-8', index=False)

Currently I am running the file through a script before hand that strips spaces from the employee_id column.

An example of employee_ids:

37 78973 3
23787
2 22 3
123

Is there a way to get csvkit to do it and save me a step?

Answer 1

You can strip() an entire Series in Pandas using .str.strip():

df1['employee_id'] = df1['employee_id'].str.strip()
df2['employee_id'] = df2['employee_id'].str.strip()

This will remove leading/trailing whitespaces on the employee_id column in both df1 and df2

Alternatively, modify the read_csv lines to use skipinitialspace=True

df1 = pd.read_csv('input1.csv', sep=',\s+', delimiter=',', encoding="utf-8", skipinitialspace=True)
df2 = pd.read_csv('input2.csv', sep=',\s,', delimiter=',', encoding="utf-8", skipinitialspace=True)

---

It looks like you are attempting to remove spaces in a string containing numbers, which can be accomplished with pandas.Series.str.replace:

df1['employee_id'] = df1['employee_id'].str.replace(" ", "")
df2['employee_id'] = df2['employee_id'].str.replace(" ", "")

Answer 2

You can do the strip() in pandas.read_csv() as:

pandas.read_csv(..., converters={'employee_id': str.strip})

And if you need to only strip leading whitespace:

pandas.read_csv(..., converters={'employee_id': str.lstrip})

And to remove all spaces:

def strip_spaces(a_str_with_spaces):
    return a_str_with_spaces.replace(' ', '')

pandas.read_csv(..., converters={'employee_id': strip_spaces})

Answer 3

Df['employee']=Df['employee'].str.strip()