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I have pandas dataframe df1 and df2 (df1 is vanila dataframe, df2 is indexed by 'STK_ID' & 'RPT_Date') :
>>> df1 STK_ID RPT_Date TClose sales discount 0 000568 20060331 3.69 5.975 NaN 1 000568 20060630 9.14 10.143 NaN 2 000568 20060930 9.49 13.854 NaN 3 000568 20061231 15.84 19.262 NaN 4 000568 20070331 17.00 6.803 NaN 5 000568 20070630 26.31 12.940 NaN 6 000568 20070930 39.12 19.977 NaN 7 000568 20071231 45.94 29.269 NaN 8 000568 20080331 38.75 12.668 NaN 9 000568 20080630 30.09 21.102 NaN 10 000568 20080930 26.00 30.769 NaN >>> df2 TClose sales discount net_sales cogs STK_ID RPT_Date 000568 20060331 3.69 5.975 NaN 5.975 2.591 20060630 9.14 10.143 NaN 10.143 4.363 20060930 9.49 13.854 NaN 13.854 5.901 20061231 15.84 19.262 NaN 19.262 8.407 20070331 17.00 6.803 NaN 6.803 2.815 20070630 26.31 12.940 NaN 12.940 5.418 20070930 39.12 19.977 NaN 19.977 8.452 20071231 45.94 29.269 NaN 29.269 12.606 20080331 38.75 12.668 NaN 12.668 3.958 20080630 30.09 21.102 NaN 21.102 7.431 I can get the last 3 rows of df2 by:
>>> df2.ix[-3:] TClose sales discount net_sales cogs STK_ID RPT_Date 000568 20071231 45.94 29.269 NaN 29.269 12.606 20080331 38.75 12.668 NaN 12.668 3.958 20080630 30.09 21.102 NaN 21.102 7.431 while df1.ix[-3:] give all the rows:
>>> df1.ix[-3:] STK_ID RPT_Date TClose sales discount 0 000568 20060331 3.69 5.975 NaN 1 000568 20060630 9.14 10.143 NaN 2 000568 20060930 9.49 13.854 NaN 3 000568 20061231 15.84 19.262 NaN 4 000568 20070331 17.00 6.803 NaN 5 000568 20070630 26.31 12.940 NaN 6 000568 20070930 39.12 19.977 NaN 7 000568 20071231 45.94 29.269 NaN 8 000568 20080331 38.75 12.668 NaN 9 000568 20080630 30.09 21.102 NaN 10 000568 20080930 26.00 30.769 NaN Why ? How to get the last 3 rows of df1 (dataframe without index) ? Pandas 0.10.1
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Drop Last Row of Pandas DataFrame Using head() Function You can also use df. head(df. shape[0] -1) to remove the last row of pandas DataFrame.
Use drop() to remove last N rows of pandas dataframe In pandas, the dataframe's drop() function accepts a sequence of row names that it needs to delete from the dataframe.
You can use df. head() to get the first N rows in Pandas DataFrame. Alternatively, you can specify a negative number within the brackets to get all the rows, excluding the last N rows.
Using the tail() function, we fetched the last 3 rows of dataframe as a dataframe and then just printed it.
Don't forget DataFrame.tail! e.g. df1.tail(10)
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