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2. How do I select rows from a DataFrame based on column values?

   stackoverflow.com/questions/17071871

   To select rows whose column value does not equal some_value, use !=: df.loc[df['column_name'] != some_value] The isin returns a boolean Series, so to select rows whose value is not in some_values, negate the boolean Series using ~: df = df.loc[~df['column_name'].isin(some_values)] # .loc is not in-place replacement.

3. Delete a column from a Pandas DataFrame - Stack Overflow

   stackoverflow.com/questions/13411544

   We can remove or delete a specified column or specified columns by the drop () method. Suppose df is a dataframe. Column to be removed = column0. Code: df = df.drop(column0, axis=1) To remove multiple columns col1, col2, . . . , coln, we have to insert all the columns that needed to be removed in a list.

4. How can I iterate over rows in a Pandas DataFrame?

   stackoverflow.com/questions/16476924

   From pandas_dataframe_iteration_vs_vectorization_vs_list_comprehension_speed_tests.svg in my eRCaGuy_hello_world repo (produced by this code). Summary. List comprehension and vectorization (possibly with boolean indexing) are all you really need. Use list comprehension (good) and vectorization (best).

5. Pretty-print an entire Pandas Series / DataFrame

   stackoverflow.com/questions/19124601

   Pandas 0.25.3 does have DataFrame.to_string and Series.to_string methods which accept formatting options. Using to_markdown. If what you need is markdown output, Pandas 1.0.0 has DataFrame.to_markdown and Series.to_markdown methods. Using to_html. If what you need is HTML output, Pandas 0.25.3 does have a DataFrame.to_html method but not a ...

6. python - Pretty Printing a pandas dataframe - Stack Overflow

   stackoverflow.com/questions/18528533

   Following up on Mark's answer, if you're not using Jupyter for some reason, e.g. you want to do some quick testing on the console, you can use the DataFrame.to_string method, which works from -- at least -- Pandas 0.12 (2014) onwards.

7. Logical operators for Boolean indexing in Pandas

   stackoverflow.com/questions/21415661

   However NumPy provides element-wise operating equivalents to these operators as functions that can be used on numpy.array, pandas.Series, pandas.DataFrame, or any other (conforming) numpy.array subclass: and has np.logical_and; or has np.logical_or; not has np.logical_not

8. How to add a new column to an existing DataFrame

   stackoverflow.com/questions/12555323

   this is a special case of adding a new column to a pandas dataframe. Here, I am adding a new feature/column based on an existing column data of the dataframe. so, let our dataFrame has columns 'feature_1', 'feature_2', 'probability_score' and we have to add a new_column 'predicted_class' based on data in column 'probability_score'.

9. Set value for particular cell in pandas DataFrame using index

   stackoverflow.com/questions/13842088

   2 22 33 52. if we want to modify the value of the cell [0,"A"] u can use one of those solution : df.iat[0,0] = 2. df.at[0,'A'] = 2. And here is a complete example how to use iat to get and set a value of cell : def prepossessing(df): for index in range(0,len(df)): df.iat[index,0] = df.iat[index,0] * 2. return df.

10. How can I get a value from a cell of a dataframe? - Stack...

    stackoverflow.com/questions/16729574

    Dataframe.iloc should be used when given index is the actual index made when the pandas dataframe is created. Avoid using dataframe.iloc on custom indices. print(df['REVIEWLIST'].iloc[df.index[1]]) Using dataframe.loc, Use dataframe.loc if you're using a custom index it can also be used instead of iloc too even the dataframe contains default ...

11. python - Convert pandas Series to DataFrame - Stack Overflow

    stackoverflow.com/questions/26097916

    You can just use a call to .reset_index() to convert a Pandas Series to a Pandas DataFrame. df = series.reset_index() The columns will not have names. To name them: df.columns = ['col name 1', 'col name 2'] (This assumes there are two columns.) answered Jun 23 at 20:26. user2138149. 15.5k 29 135 269.