PYTHON: Splitting One Column into Multiple After Deleting some rows

Question

I am pretty new to Python and I am trying to cleanse some data. I\'ve attached a link to the data file (Two tabs: Raw data and desired outcome). Please help!

What I am t

Answer 1

To split a column into 2 columns with pandas

d = pd.read_csv('file.csv')

   col_1
    "val1-val2"
    "valA-valB"

df = pd.DataFrame(d.col_1.str.split("-",1).tolist(),columns = ['A','B'])

      A     B
0  val1  val2
1  valA  valB

Answer 2

Use:

# Read the excel file with sheet_name='Raw data' and skiprows=23 which are not necessary
data_xls = pd.read_excel("Example2.xlsx", sheet_name='Raw data', skiprows=23)

# Create the dummy columns names which are similar to desired output column
dummy_col_names = ['Internal Link Tracking (non','Campaign Name','Creative','Action','Action 2']
# Use str.split with expand=True to create a dataframe
dummy_df = data_xls['Internal Link Tracking (non-promotions) - ENT (c20)'].str.split('-',expand = True)
# Rename columns as per dummy column list
dummy_df.columns = dummy_col_names

# Drop the column which is not necessary
data_xls.drop('Internal Link Tracking (non-promotions) - ENT (c20)', axis=1, inplace=True)

# Use pd.concat along axis=1 to concat both data_xls and dummy_df along columns
data_xls = pd.concat((data_xls,dummy_df),sort=False,axis=1)

# To preserve oreder similar to desired output column use the following code
col_names = data_xls.columns.tolist()
data_xls = data_xls[col_names[:1]+dummy_col_names+col_names[1:-5]]

Answer 3

Try this:

1.)Delete Row 1-23

df = pd.read_excel('/home/mayankp/Downloads/Example2.xlsx', sheet_name=0, index_col=None, header=None, skiprows=23)

2.) Split Column B into multiple columns using '-' as a delimiter and 3.)Assign Column names to the new columns

Both these steps can be done in 1 go:

sub_df = df[1].str.split('-', expand=True).rename(columns = lambda x: "string"+str(x+1))

In [179]: sub_df
Out[179]: 
                       string1       string2             string3      string4     string5
1                           us      campaign            article1   scrolldown  findoutnow
2                           us      campaign            article1  scrollright        None
3                           us      campaign            article1   findoutnow        None
4                           us      campaign  payablesmanagement   findoutnow        None

Above is how the sample looks like after splitting on -.

Now drop the actual column from df and insert these new columns in it:

df = df.drop(1, axis=1)
df = pd.concat([df,sub_df], axis=1)

4.)Keep the numeric columns

Remaining columns are already intact. No change needed for this.

Let me know if this helps.