如何在数据帧中为python中的特定行值选择列数据？

Question

As the question says, I have a data frame which is quite large but looks like:

        ID    Count    ValueX    Value 2    Value 3
RowX    1      234.     255.       yes.      yes
RowY    1      123.     135.       543.      342
RowW    1      234.     235.       yes.      yes
RowJ    1      123.     115.       543.      342
RowA    1      234.     285.       yes.      yes
RowR    1      123.     165.       543.      342
RowX    2      234.     255.       yes.      yes
RowY    2      123.     135.       543.      342
RowW    2      234.     235.       yes.      yes
RowJ    2      123.     115.       543.      342
RowA    2      234.     285.       yes.      yes
RowR    2      123.     165.       543.      342
.
.
.
RowX    1233   234.     255.       yes.      yes
RowY    1233   123.     135.       543.      342
RowW    1233   234.     235.       yes.      yes
RowJ    1233   123.     115.       543.      342
RowA    1233   234.     285.       yes.      yes
RowR    1233   123.     165.       543.      342

What I want is to be able to select all the values in column ValueX where the row is RowX for each of the ID numbers 1-1233 and return them in a list.

Answer 1

df.query('1 <= ID <= 1233').loc['RowX', 'ValueX']

RowX    255.0
RowX    255.0
RowX    255.0
Name: ValueX, dtype: float64

Answer 2

IIUC:

In [30]: df.loc[df.index.isin(['RowX']) & df['ID'].between(1, 1233), 'ValueX'].tolist()
Out[30]: [255.0, 255.0, 255.0]

Answer 3

filtered_df = df[(df.ID.between(1, 1233)) & (df.index == 'RowX')][['ValueX']]

values_list = filtered_df.ValueX.tolist()