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  • python - How to delete rows from a pandas DataFrame based on a . . .
    If you want to drop rows of data frame on the basis of some complicated condition on the column value then writing that in the way shown above can be complicated I have the following simpler solution which always works Let us assume that you want to drop the column with 'header' so get that column in a list first text_data = df['name'] tolist()
  • Remove rows from pandas DataFrame based on condition
    There's no difference for a simple example like this, but if you starting having more complex logic for which rows to drop, then it matters For example, delete rows where A=1 AND (B=2 OR C=3) Here's how you use drop() with conditional logic: df drop( df query(" `Species`=='Cat' ") index) This is a more scalable syntax for more complicated logic
  • Drop rows on multiple conditions in pandas dataframe
    Drop rows on condition in pandas dataframe 4 python, pandas, drop rows by condition 0 pandas how to
  • python, pandas, drop rows by condition - Stack Overflow
    hello I need help to drop some rows by the condition: if the estimated price minus price is more than 1500 (positive) drop the row price estimated price 0 13295 13795 1 19990 22275 2 7295 6498 for example only the index 1 would be drop thank you!
  • delete rows based on a condition in pandas - Stack Overflow
    The best is boolean indexing but need invert condition - get all values equal and higher as 72: print (df[df["coverage"] >= 72]) coverage name reports year Pima 214 Molly 24 2012 Santa Cruz 212 Tina 31 2013 Maricopa 72 Jake 2 2014 Yuma 85 Amy 3 2014
  • python - Conditional dropna () pandas - Stack Overflow
    I have a rather simple question: I want to drop rows from a DataFrame based on a condition The DataFrame looks something like this: Program act Original RO A Original RO nan Followup RO B Followup RO nan Integral RO nan I want to delete nulls for Original RO and Integral RO Programs only So it should look like this:
  • dropping rows from dataframe based on a not in condition
    I want to drop rows from a pandas dataframe when the value of the date column is in a list of dates The following code doesn't work: a=['2015-01-01' , '2015-02-01'] df=df[df datecolumn not in a] I get the following error: ValueError: The truth value of a Series is ambiguous Use a empty, a bool(), a item(), a any() or a all()
  • How to drop rows from pandas data frame that contains a particular . . .
    If your string constraint is not just one string you can drop those corresponding rows with: df = df[~df['your column'] isin(['list of strings'])] The above will drop all rows containing elements of your list NB: This will only work for exact string matches; for partial matches see other answers (e g Rupert Schiessl)
  • Deleting rows based on multiple conditions in a pandas dataframe
    drop could be used to drop rows The most obvious way is to constructing a boolean mask given the condition, filter the index by it to get an array of indices to drop and drop these indices using drop() If the condition is: Row with value of col 'one', 'two', or 'three' greater than 0; and value of col 'four' less than 0 should be deleted
  • Pandas DataFrame to drop rows in the groupby - Stack Overflow
    How about if I want to filter out the rows in groupby in term of the total count() in date category For example, I want to count() for a date larger than 15000 The table I want likes this:





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