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handling missing values in python

Coder Cuttlefish answered on October 26, 2022 Popularity 9/10 Helpfulness 3/10

answer handling missing values in python

related missing values python

handling missing values in python

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colors = {red: "#FF0000", green: "#00FF00", blue: "#0000FF"}
colors.get("yellow", "#FFFF00") # returns "#FFFF00"

# deeply nested values

dic = {nested1: {key1: val1, key2: val2}}
dic.get("nested2", {}).get(key3, "fallback") 
"""
If "nested2" exists, we call get() on it and retrieve the value of "key3", or
"fallback" if key3 does not exist. If "nested2" does not exist, we call get() on {},
which would return "fallback"
"""

Popularity 9/10 Helpfulness 3/10 Language python

Source: Grepper

Tags: python

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Contributed on Oct 26 2022

Coder Cuttlefish

0 Answers Avg Quality 2/10

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missing values python

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# Show number of missing data
df.isna().sum()

# Visualize missing data information
import missingno as msno
import matplotlib.pyplot as plt
msno.matrix(airquality)
plt.show()

# Drop missing data
df_dropped = df.dropna(subset = ['col'])

# Replace/impute missing data with single value
col_mean = df['col'].mean()
df_imputed = df.fillna({'col': col_mean})

# Replace/impute missing data with series
series_imp = df['col1'] * 5
df_imputed = df.fillna({'col2':series_imp})

# Missing values are not always "NaN". They can be blank, "?" or other symbols (rarely)
# Check for values through manual validations first
df["col"].value_counts() # Look out for suspicious values
# Determine number of missing values in a column
df.isna().any()
df['col'].isnull().sum()
# Drop missing values
df.dropna(axis = 0) # Drop entire row for missing value (default)
df.dropna(axis = 1) # Drop entire column for missing value
# Drop missing values for specific column
df.dropna(subset = ["col"], axis = 0)
# Replace missing values
df["col"].replace(np.nan, new_val)
df.fillna(0)

Popularity 9/10 Helpfulness 5/10 Language python

Source: Grepper

Tags: python py

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Contributed on Jan 29 2023

Innocent Iguana

0 Answers Avg Quality 2/10

handling missing values in python

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