Hi, Here is the solution
e) To drop entire row, use dropna() function
example :
df.dropna()
To drop entire colum, use dropna() with axis parameter as follows
df.dropna(axis=1)
f) To replace null, you can use fillna()
for example:
consider "Name" is the column in df to be checked for null
df["Name"].fillna("No Name", inplace=True)
sample code
import pandas as pd
data = [["A", None, 10], ["B", "B@live.in", 20], ["C", None, 30], [None, "c.@live.in", None], ["D", "D@live.in", 23]]
df = pd.DataFrame(data, columns=["Name", "email", "age"])
print(df) df["Name"].fillna("No Name", inplace=True)
print(df) print(df.isnull())
print(df.dropna())
print(df.dropna(axis=1)) |
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