df.dropna(inplace=True)
# to drop any rows that contain any null values
df.dropna(how='all', inplace=True)
# to drop the rows wich all of it's values is any
# if you want to drop the columns not the rows you just set the axis to 1 like this:
df.dropna(axis=1, inplace=True)
import pandas as pd
# Create a Dataframe from a CSV
df = pd.read_csv('example.csv')
# Drop rows with any empty cells
df.dropna(
axis=0,
how='any',
thresh=None,
subset=None,
inplace=True
)
df.dropna(subset=['Column name'])
df.dropna()
df = df[df['EPS'].notna()]
df.dropna(inplace=True)
df=df.interpolate(method='pad', limit=3)