I am having a large data(image:https://drive.google.com/file/d/1TFX1LQhQ-xwYp47fllL8PWwbwbv3wsb6/view?usp=drivesdk).The shape of data is 10000x100 .I want to remove irrelevant data by the condition(-0.5 =<angle<= 0.8).
the angle is a list of Angle_0,Angle_1,Angle_2......Angle_20.

ang = [f"Angle_{i}" for i in range(20)]

I want to have rows which follows the condition(-0.5 =<angle<= 0.8) for angle and delete other rows.

How to do this in python and pandas?

for example Angle_0 has value 0.1926715(row number 24) i want that row of entire dataset then in Angle_1 have data such as 0.1926715,0.192497 and i need those row(row number 7,9,14,16,19,21,23,26,28,29) similary for all other angles

I am a beginner in python. Thank you very much in advance.

CodePudding user response：

new_df = df[(df['angle']>=-0.5 and df['angle']<=0.8]

CodePudding user response：

If you need to remove the rows that contain at least one angle that does not follow your conditions, this will solve your problem:

df.loc[(df>=-0.5 & df<=0.8).all(axis=1)]