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How do I get the row count of a Pandas DataFrame? could use df info () so you get row count (# entries), number of non-null entries in each column, dtypes and memory usage Good complete picture of the df If you're looking for a number you can use programatically then df shape [0]
How to get set a pandas index column title or name? To just get the index column names df index names will work for both a single Index or MultiIndex as of the most recent version of pandas As someone who found this while trying to find the best way to get a list of index names + column names, I would have found this answer useful:
python - Renaming column names in Pandas - Stack Overflow To focus on the need to rename of replace column names with a pre-existing list, I'll create a new sample dataframe df with initial column names and unrelated new column names
Creating an empty Pandas DataFrame, and then filling it df loc[len(df)] = [a, b, c] As before, you have not pre-allocated the amount of memory you need each time, so the memory is re-grown each time you create a new row It's just as bad as append, and even more ugly Empty DataFrame of NaNs And then, there's creating a DataFrame of NaNs, and all the caveats associated therewith
python - What is df. values [:,1:]? - Stack Overflow 0 df values is gives us dataframe values as numpy array object df values [:, 1:] is a way of accessing required values with indexing It means all the rows and all columns except 0th index column in dataframe
Detect and exclude outliers in a pandas DataFrame import pandas as pd import numpy as np from scipy import stats df = pd DataFrame(np random randn(100, 3)) df[(np abs(stats zscore(df)) < 3) all(axis=1)] Description: For each column, it first computes the Z-score of each value in the column, relative to the column mean and standard deviation It then takes the absolute Z-score because the direction does not matter, only if it is below the