# Find the maximum value in the DataFrame
max_value = df.max().max()
# find column and index
max_location = df.stack().idxmax()
column_name = max_location[1]
index_value = max_location[0]

# Alternative approach
# Flatten the DataFrame and sort the values
flat_df = df.unstack().reset_index()
flat_df.columns = ['Column', 'Index', 'Value']
# Sort by value and get the second largest
second_largest = flat_df.nlargest(2, 'Value').iloc[1]
# Retrieve the column name and index
column_name = second_largest['Column']
index_value = second_largest['Index']
second_largest_value = second_largest['Value']

Popularity 7/10 Helpfulness 6/10 Language python

Source: Grepper

Tags: pandas python row ro

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Contributed on Jun 11 2024

Innocent Iguana

0 Answers Avg Quality 2/10

pandas dataframe get row with max value in column

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df[df['Score'] == df['Score'].max()]

Popularity 8/10 Helpfulness 4/10 Language python

Source: Grepper

Tags: dataframe get

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Contributed on Jul 19 2023

orci

0 Answers Avg Quality 2/10

pandas find column with max value for each row

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-1

# credit to Stack Overflow in the source link

df.head()
Communications and Search   Business    General Lifestyle
0   0.745763    0.050847    0.118644    0.084746
0   0.333333    0.000000    0.583333    0.083333
0   0.617021    0.042553    0.297872    0.042553
0   0.435897    0.000000    0.410256    0.153846
0   0.358974    0.076923    0.410256    0.153846

df.idxmax(axis=1)
0    Communications
1          Business
2    Communications
3    Communications
4          Business
dtype: object

Popularity 10/10 Helpfulness 2/10 Language python

Source: stackoverflow.com

Tags: each

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Contributed on May 28 2021

wolf-like_hunter

0 Answers Avg Quality 2/10

pandas select row with max value in column

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