I have an excel-sheet which has a lot of unneccessary information. Therefore I would like to filter out only those rows which contain specific values from a dataframe. However, the dataframe has no column names and I will need to filter the rows with the certain values from multiple dataframes with possibly different amounts of columns.
Therefore I like to filter the rows out based on their values but without knowing the column name.

The accent of this question is on the words names and in place, because I want to drop columns having equal names (no matter the values) but I don’t want to drop columns having equal values but different names, and I want do it efficiently.

I have a pretty simple pandas DataFrame and I want to select the portion of the DataFrame that has data within a column that contains within it another string

Closed 2 days ago.

Example data:

I’m having trouble modifying a new column.

I want to get the information per Name.

I have a Pandas Dataframe with 4 different columns: an ID, country, team and a color that is assigned to each player following a specific order.

I have a Pandas Dataframe with 4 different columns: an ID, country, team and a color that is assigned to each player following a specific order.

I have a dataset which is in a txt.file but when i read it using pandas it gets into one colunm.
for example: