WebJan 29, 2024 · This is not a correct answer. This would also return rows which index is equal to x (i.e. '2002-1-1 01:00:00' would be included), whereas the question is to select rows which index is larger than x. @bennylp Good point. To get strictly larger we could use a +epsilon e.g. pd.Timestamp ('2002-1-1 01:00:00.0001') WebJan 20, 2016 · Result: dataframe. which (df == "2") #returns rowIndexes results from the entire dataset, in this case it returns a list of 3 index numb. Result: 5 13 17. length (which (df == "2")) #count numb. of rows that matches a condition. Result: 3. You can also do this column wise, example of:
Pandas: Get Index of Rows Whose Column Matches Value
WebDec 9, 2024 · .iloc selects rows based on an integer index. So, if you want to select the 5th row in a DataFrame, you would use df.iloc[[4]] since the first row is at index 0, the … WebNov 5, 2024 · We can use pd.Index.get_indexer to get integer index. idx = df.index.get_indexer (list_of_target_labels) # If you only have single label we can use tuple unpacking here. [idx] = df.index.get_indexer ( [country_name]) NB: pd.Index.get_indexer takes a list and returns a list. Integers from 0 to n - 1 indicating that the index at these … circle related formula
Find index of all rows with null values in a particular column in ...
WebAug 3, 2024 · There is a difference between df_test['Btime'].iloc[0] (recommended) and df_test.iloc[0]['Btime']:. DataFrames store data in column-based blocks (where each block has a single dtype). If you select by column first, a view can be returned (which is quicker than returning a copy) and the original dtype is preserved. In contrast, if you select by … WebNov 27, 2024 · The new dataframe that I want is: 1) find the rows with the same index; 2) calculate the average value of the corresponding rows in column 'A'. df_new = A_average Name apple 0 banana 2.5 This is because: df1 and … WebJul 16, 2024 · You can use the following syntax to get the index of rows in a pandas DataFrame whose column matches specific values: df. index [df[' column_name '] ... Note that we can also use the less than and greater than operators to find the index of the rows where one column is less than or greater than a certain value: circle rein bangkok