Append an empty row in dataframe using pandas

Question

I am trying to append an empty row at the end of dataframe but unable to do so  even trying to understand how pandas work with append function and still not getting it   Here s the code   import pandas as pd  excel names     ARMANI EMPORIO AR0143-book xlsx   excels    pd ExcelFile name  for name in excel names  frames    x parse x sheet names 0   header None index col None  dropna how  all   for x in excels  for f in frames      f append 0  float  NaN        f append 2  float  NaN      There are two columns and random number of row   with  print f  in for loop i Get this                                0                 1 0                   Brand Name    Emporio Armani 2                 Model number            AR0143 4                  Part Number            AR0143 6                   Item Shape       Rectangular 8   Dial Window Material Type           Mineral 10               Display Type          Analogue 12                 Clasp Type            Buckle 14               Case Material   Stainless steel 16              Case Diameter    31 millimetres 18               Band Material           Leather 20                 Band Length  Women s Standard 22                 Band Colour             Black 24                 Dial Colour             Black 26            Special Features       second-hand 28                    Movement            Quartz

User · Answer

You can add it by appending a Series to the dataframe as follows  I am assuming by blank you mean you want to add a row containing only  Nan   You can first create a Series object with Nan  Make sure you specify the columns while defining  Series  object in the -Index parameter  The you can append it to the DF  Hope it helps   from numpy import nan as Nan import pandas as pd   gt  gt  gt  df1   pd DataFrame   A     A0    A1    A2    A3                             B     B0    B1    B2    B3                             C     C0    C1    C2    C3                             D     D0    D1    D2    D3                             index  0  1  2  3     gt  gt  gt  s2   pd Series  Nan Nan Nan Nan   index   A    B    C    D     gt  gt  gt  result   df1 append s2   gt  gt  gt  result      A    B    C    D 0   A0   B0   C0   D0 1   A1   B1   C1   D1 2   A2   B2   C2   D2 3   A3   B3   C3   D3 4  NaN  NaN  NaN  NaN

User · Answer

The code below worked for me   df append pd Series  np nan    ignore index   True

User · Answer

Assuming your df index is sorted you can use   df loc df index max     1    None   It handles well different indexes and column types     EDIT  it works with pd DatetimeIndex if there is a constant frequency  otherwise we must specify the new index exactly e g   df loc df index max     pd Timedelta milliseconds 1     None   long example   df   pd DataFrame   pd Timestamp 12432423   23   text field                          columns   timestamp    speed    text                        index pd DatetimeIndex start  2111-11-11  freq  ms   periods 1   df info      lt class  pandas core frame DataFrame  gt  DatetimeIndex  1 entries  2111-11-11 to 2111-11-11 Freq  L Data columns  total 3 columns   timestamp    1 non-null datetime64 ns  speed        1 non-null int64 text         1 non-null object dtypes  datetime64 ns  1   int64 1   object 1  memory usage  32 0  bytes  df loc df index max     1    None df info      lt class  pandas core frame DataFrame  gt  DatetimeIndex  2 entries  2111-11-11 00 00 00 to 2111-11-11 00 00 00 001000 Data columns  total 3 columns   timestamp    1 non-null datetime64 ns  speed        1 non-null float64 text         1 non-null object dtypes  datetime64 ns  1   float64 1   object 1  memory usage  64 0  bytes  df head                                timestamp                   speed      text 2111-11-11 00 00 00 000 1970-01-01 00 00 00 012432423   23 0    text field 2111-11-11 00 00 00 001 NaT NaN NaN

User · Answer

Append  empty  row to data frame and fill selected cells   Generate empty data frame  no rows just columns a and b    import pandas as pd     col names      a   b   df    pd DataFrame columns   col names    Append empty row at the end of the data frame   df   df append pd Series    ignore index   True    Now fill the empty cell at the end  len df -1  of the data frame in column a   df loc  len df -1   a     123   Result        a    b 0  123  NaN     And of course one can iterate over the rows and fill cells   col names      a   b   df    pd DataFrame columns   col names  for x in range 0 5       df   df append pd Series    ignore index   True      df loc  len df -1   a     123   Result        a    b 0  123  NaN 1  123  NaN 2  123  NaN 3  123  NaN 4  123  NaN

User · Answer

You can add a new series  and name it at the same time  The name will be the index of the new row  and all the values will automatically be NaN   df append pd Series name  Afterthought

User · Answer

Add a new pandas Series using pandas DataFrame append      If you wish to specify the name  AKA the  index   of the new row  use   df append pandas Series name  NameOfNewRow      If you don t wish to name the new row  use   df append pandas Series    ignore index True    where df is your pandas DataFrame

User · Answer

Assuming df is your dataframe   df prime   pd concat  df  pd DataFrame   np nan    df shape 1    columns df columns    ignore index True    where df prime equals df with an additional last row of NaN s   Note that pd concat is slow so if you need this functionality in a loop  it s best to avoid using it  In that case  assuming your index is incremental  you can use  df loc df iloc -1  name   1      np nan

User · Answer

You can also use   your dataframe insert loc 0  value np nan  column       where loc is your empty row index

[python] Append an empty row in dataframe using pandas

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