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How do you combine two columns into a new column in a dataframe made of two or more different csv files?


How do you combine two columns into a new column in a dataframe made of two or more different csv files?

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How do you combine two columns into a new column in a dataframe made of two or more different csv files?
Tag : r , By : Steve
Date : November 24 2020, 03:41 PM


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Combine columns in a Pandas DataFrame to a column of lists in a DataFrame


Tag : python , By : Bharath
Date : March 29 2020, 07:55 AM
around this issue Consider the following DataFrame. , You can do it in one line like this:
>>> df['v6'] = df[['v2', 'v3', 'v4']].mul(df['v5'], axis=0).values.tolist()
>>> df
   v1  v2  v3  v4  v5            v6
0   1   2   3   4   5  [10, 15, 20]
1   1   2   3   4   5  [10, 15, 20]
2   1   2   3   4   5  [10, 15, 20]

How to combine columns and pivot column values into new column at the same time within dataframe?


Tag : python-3.x , By : Tonci Grgin
Date : March 29 2020, 07:55 AM
like below fixes the issue Okay let's try this bit of code for those column naming. First, rename your columns to move the incremented index to after a separator, ':' I choose. Then use pd.wide_to_long to reshape the dataframe and lastly filter the dataframe to choose only the "value" columns.
df.columns = df.columns.str.replace(r'(\d+)_(\w+)',r'\2:\1')
pd.wide_to_long(df.reset_index(),
                ['0_type','1_type','0_value','1_value','firstname_value','lastname_value'],
                'index',
                'Num',
                sep=':')\
  .reset_index()\
  .filter(like='value')
    0_value  1_value firstname_value lastname_value
0         1        2           test1          test1
1         2   email1             NaN            NaN
2         3   email2             NaN            NaN
3         4   email3           test2          test2
4         5   email4             NaN            NaN
5         6   email5           test3          test3
6         7   email6           test4          test4
7         8   email7           test5          test5
8         9   email8           test6          test6
9        10   email9           test7          test7
10       11  email10           test8          test8
11       12  email11           test9          test9
12       13  email12          test10         test10
13       14  email13          test11         test11
14       15  email14          test12         test12
15       16  email15          test13         test13
16       17  email16          test14         test14
17       18  email17          test15         test15

All my columns are in row format. How can i change the dataframe to have each row made into a column, based on each Team


Tag : r , By : micaleel
Date : March 29 2020, 07:55 AM
With these it helps I'm trying to clean some data for some soccer analysis I wanted to do. My problem is that I can't figure out how to properly change my dataframe. Without a picture, there's really nothing I can do to properly explain it. , Create the dataframe for demo purposes
df <- structure(
  list(
    Measure.Names = structure(
      c(1L, 1L, 1L, 1L, 2L,
        2L, 2L, 2L),
      .Label = c("Over Perform XG - Defense", "Over Perform XG - Offense"),
      class = "factor"
    ),
    Team = structure(
      c(4L, 3L, 2L, 1L, 4L,
        3L, 2L, 1L),
      .Label = c(
        "Bournemouth",
        "Brighton and Hove Albion",
        "Burnley",
        "Cardiff City"
      ),
      class = "factor"
    ),
    Measure.Values = structure(
      1:8,
      .Label = c("1",
                 "2", "3", "4", "5", "6", "7", "8"),
      class = "factor"
    )
  ),
  class = "data.frame",
  row.names = c(NA,-8L)
)

df
#>               Measure.Names                     Team Measure.Values
#> 1 Over Perform XG - Defense             Cardiff City              1
#> 2 Over Perform XG - Defense                  Burnley              2
#> 3 Over Perform XG - Defense Brighton and Hove Albion              3
#> 4 Over Perform XG - Defense              Bournemouth              4
#> 5 Over Perform XG - Offense             Cardiff City              5
#> 6 Over Perform XG - Offense                  Burnley              6
#> 7 Over Perform XG - Offense Brighton and Hove Albion              7
#> 8 Over Perform XG - Offense              Bournemouth              8
tidyr::spread(df, Measure.Names, Measure.Values)
#>                       Team Over Perform XG - Defense
#> 1              Bournemouth                         4
#> 2 Brighton and Hove Albion                         3
#> 3                  Burnley                         2
#> 4             Cardiff City                         1
#>   Over Perform XG - Offense
#> 1                         8
#> 2                         7
#> 3                         6
#> 4                         5

Combine two or more columns in a dataframe into a new column with a new name


Tag : r , By : lili
Date : March 29 2020, 07:55 AM

Combine values of two columns of dataframe into one column


Tag : python , By : Bin
Date : September 21 2020, 08:00 PM
I hope this helps . hi I want to append two column values into a single column, something like shown below in pandas. Can anyone help me out in doing that? , pd.wide_to_long should work:
df['value'] = list(range(0,2))
pd.wide_to_long(df, stubnames=['t', 'v'], i='value', j='dropme', sep='').reset_index().drop(columns=['value', 'dropme'])                                                           

       t  v
0   0.00  1
1   0.42  1
2  10.00 -1
3   0.78 -1
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