如何使用列索引删除第一列中以特定字符串开头的 Dataframe 行

Question

I am transposing a data frame where I do not have defined column names and then need to drop rows from the transposed table where a given rows value in the first column (index 0) starts with 'zrx'. I am thinking something like this should work, but can't seem to get it working:

df[~df[0].str.startswitg("zrx")]

Input data looks like this (no headers):

Index 0    Index 1
zrx456.       True
zrx567        false
abc234      True
Gfh123       False
nbv345       True
zrx456         False
zrx668        True
zrx789         True

My goal is to return this data frame with only the rows that start with zrx in column 0.

Answer 1

If you know the name of the first column, use

df[~df.Artist.str.startswith('zrx')]

If you do not know the name of the first column, use

df[~df.iloc[:,0].str.startswith('zrx')]

input

Artist  Album   Point
0   zrxAC1  A   1
1   AC2     B   2
2   zrxAC1  NaN     3
3   AC4     A   4
4   AC5     C   5

Output

Artist  Album   Point
1   AC2     B   2
3   AC4     A   4
4   AC5     C   5