WebApr 11, 2024 · 1 Answer. Sorted by: 1. There is probably more efficient method using slicing (assuming the filename have a fixed properties). But you can use os.path.basename. It will automatically retrieve the valid filename from the path. data ['filename_clean'] = data ['filename'].apply (os.path.basename) Share. Improve this answer. Webproperty DataFrame.loc [source] #. Access a group of rows and columns by label (s) or a boolean array. .loc [] is primarily label based, but may also be used with a boolean array. Allowed inputs are: A single label, e.g. 5 or 'a', (note that 5 is interpreted as a label of the index, and never as an integer position along the index).
How To Read CSV Files In Python (Module, Pandas, & Jupyter …
WebCreate a multi-dimensional cube for the current DataFrame using the specified columns, so we can run aggregations on them. DataFrame.describe (*cols) Computes basic statistics for numeric and string columns. DataFrame.distinct () Returns a new DataFrame containing the distinct rows in this DataFrame. WebAug 30, 2024 · Use a list of values to select rows from a Pandas dataframe. 1537. How to change the order of DataFrame columns? 2116. Delete a column from a Pandas DataFrame. 1775. How do I get the row count of a Pandas DataFrame? 3830. How to iterate over rows in a DataFrame in Pandas. 3310. can employers see your email on glassdoor
pandas.DataFrame.where — pandas 2.0.0 documentation
WebSep 17, 2024 · Pandas where () method is used to check a data frame for one or more condition and return the result accordingly. By default, The rows not satisfying the … 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 second row is at index 1, and so on..loc selects rows based on a labeled index. So, if you want to select the row with an index label of 5, you would directly use df.loc[[5]]. WebDec 19, 2016 · So, applied to your dataframe: In [1]: a[a['c2'] == 1].index[0] In [2]: a[a['c1'] > 7].index[0] Out[1]: 0 Out[2]: 4 Where the query returns more than one row, the additional index results can be accessed by specifying the desired index, e.g. .index[n] fist cartoon drawing