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chevron_left Row and Column Operations Cookbook
Adding a column that contains the difference in consecutive rowsAdding a constant number to DataFrame columnsAdding an empty column to a DataFrameAdding column to DataFrame with constant valuesAdding new columns to a DataFrameAppending rows to a DataFrameApplying a function that takes as input multiple column valuesApplying a function to a single column of a DataFrameChanging column type to categoricalChanging the name of a DataFrame's indexChanging the order of columns in a DataFrameChanging the type of a DataFrame's indexChanging the type of a DataFrame's columnChecking if a column exists in a DataFrameChecking if a DataFrame column contains some valuesChecking if a value exists in a DataFrame in PandasChecking if column is numericChecking the data type of columnsChecking whether column values match or contain a patternCombining two columns as a single column of tuplesCombining two columns of type string in a DataFrameComputing the average of columnsComputing the correlation between columnsConcatenating DataFrames horizontallyConcatenating DataFrames verticallyConverting a row to column labelsConverting categorical type to intConverting column to listConverting Index to listConverting percent strings into numericConverting the index of a DataFrame into a columnCounting duplicate rowsCounting number of rows with no missing valuesCounting the occurrence of values in columnsCounting unique values in a column of a DataFrameCounting unique values in rows of a DataFrameCreating a new column based on other columnsCreating new column using if, elif and elseDescribing certain columnsDropping columns whose label contains a substringGetting column values based on another column values in a DataFrame in PandasGetting columns as a copyGetting columns whose label contains a substringGetting maximum value in columnsGetting maximum value of entire DataFrameGetting mean of columnsGetting median of columnsGetting minimum value in columnsGetting row label when calling applyGetting row labels as listGetting rows where column value contains any substring in a listGetting the name of indexGetting type of indexGrouping DataFrame rows into listsInserting column at a specific locationIterating over each column of a DataFrameIterating over each row of a DataFrameModifying rows of a DataFrameModifying values in IndexRemoving columns from a DataFrameRemoving columns using column labelsRemoving columns using integer indexRemoving columns with all missing valuesRemoving columns with some missing valuesRemoving duplicate columnsRemoving duplicate rowsRemoving first n rows of a DataFrameRemoving multiple columnsRemoving prefix from column labelsRemoving rows at random without shufflingRemoving rows from a DataFrame based on column valuesRemoving rows using integer indexRemoving rows with all zerosRemoving suffix from column labelsRenaming columns of a DataFrameReplacing substring in column valuesReturning multiple columns using the apply functionReversing the order of rowsSetting a new index of a DataFrameSetting an existing column as the new indexSetting column as the indexSetting integers as column labelsShowing all column labelsShuffling the rows of a DataFrameSorting a DataFrame by columnSorting a DataFrame by indexSorting DataFrame alphabeticallySorting DataFrame by column labelsSplitting a column of strings into multiple columnsSplitting column of lists into multiple columnsSplitting dictionary into separate columnsStripping substrings from values in columnsStripping whitespace from columnsStripping whitespaces in column labelsSumming a column of a DataFrameSumming rows of specific columnsSwapping the rows and columns of a DataFrameUpdating a row while iterating over the rows of a DataFrameUpdating rows based on column valuesUsing apply method in parallel
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chevron_left Row and Column Operations Cookbook
Adding a column that contains the difference in consecutive rowsAdding a constant number to DataFrame columnsAdding an empty column to a DataFrameAdding column to DataFrame with constant valuesAdding new columns to a DataFrameAppending rows to a DataFrameApplying a function that takes as input multiple column valuesApplying a function to a single column of a DataFrameChanging column type to categoricalChanging the name of a DataFrame's indexChanging the order of columns in a DataFrameChanging the type of a DataFrame's indexChanging the type of a DataFrame's columnChecking if a column exists in a DataFrameChecking if a DataFrame column contains some valuesChecking if a value exists in a DataFrame in PandasChecking if column is numericChecking the data type of columnsChecking whether column values match or contain a patternCombining two columns as a single column of tuplesCombining two columns of type string in a DataFrameComputing the average of columnsComputing the correlation between columnsConcatenating DataFrames horizontallyConcatenating DataFrames verticallyConverting a row to column labelsConverting categorical type to intConverting column to listConverting Index to listConverting percent strings into numericConverting the index of a DataFrame into a columnCounting duplicate rowsCounting number of rows with no missing valuesCounting the occurrence of values in columnsCounting unique values in a column of a DataFrameCounting unique values in rows of a DataFrameCreating a new column based on other columnsCreating new column using if, elif and elseDescribing certain columnsDropping columns whose label contains a substringGetting column values based on another column values in a DataFrame in PandasGetting columns as a copyGetting columns whose label contains a substringGetting maximum value in columnsGetting maximum value of entire DataFrameGetting mean of columnsGetting median of columnsGetting minimum value in columnsGetting row label when calling applyGetting row labels as listGetting rows where column value contains any substring in a listGetting the name of indexGetting type of indexGrouping DataFrame rows into listsInserting column at a specific locationIterating over each column of a DataFrameIterating over each row of a DataFrameModifying rows of a DataFrameModifying values in IndexRemoving columns from a DataFrameRemoving columns using column labelsRemoving columns using integer indexRemoving columns with all missing valuesRemoving columns with some missing valuesRemoving duplicate columnsRemoving duplicate rowsRemoving first n rows of a DataFrameRemoving multiple columnsRemoving prefix from column labelsRemoving rows at random without shufflingRemoving rows from a DataFrame based on column valuesRemoving rows using integer indexRemoving rows with all zerosRemoving suffix from column labelsRenaming columns of a DataFrameReplacing substring in column valuesReturning multiple columns using the apply functionReversing the order of rowsSetting a new index of a DataFrameSetting an existing column as the new indexSetting column as the indexSetting integers as column labelsShowing all column labelsShuffling the rows of a DataFrameSorting a DataFrame by columnSorting a DataFrame by indexSorting DataFrame alphabeticallySorting DataFrame by column labelsSplitting a column of strings into multiple columnsSplitting column of lists into multiple columnsSplitting dictionary into separate columnsStripping substrings from values in columnsStripping whitespace from columnsStripping whitespaces in column labelsSumming a column of a DataFrameSumming rows of specific columnsSwapping the rows and columns of a DataFrameUpdating a row while iterating over the rows of a DataFrameUpdating rows based on column valuesUsing apply method in parallel
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Counting the occurrence of values in columns of a Pandas DataFrame

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Row and Column Operations Cookbook
schedule Mar 9, 2022
Last updated
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Counting occurrence of a single value in a column

Consider the following DataFrame:

df = pd.DataFrame({"A":["a","b","a"]})
df
A
0 a
1 b
2 a

Solution

To count the number of times the value "a" occurs in column A:

(df["A"] == "a").sum()
2

Explanation

To break this down, we are first fetching a Series of booleans where True indicates a match:

(df["A"] == "a")
0 True
1 False
2 True
Name: A, dtype: bool

Since the internal representation of a True is 1, and False is 0, we can simply take the sum of this Series to count the total occurrence:

(df["A"] == "a").sum()
2

Counting occurrence of a single value in multiple columns

Consider the following DataFrame:

df = pd.DataFrame({"A":["a","b","a"],"B":["a","a","a"]})
df
A B
0 a a
1 b a
2 a a

Solution

To get the number of "a" in each column:

(df == "a").sum()
A 2
B 3
dtype: int64

The idea is the exact same as that of the single-column case above.

Counting occurrences of multiple values in a column

Consider the following DataFrame:

df = pd.DataFrame({"A":["a","b","a","c"]})
df
A
0 a
1 b
2 a
3 c

Solution

To count the occurrences of multiple values in column A:

values = ["a","b"]
counts = df["A"].value_counts()
counts[values].sum()
3

Explanation

We first obtain a frequency count of the values in column A using Series' value_counts():

counts = df["A"].value_counts()   # returns a Series
counts
a 2
c 1
b 1
Name: A, dtype: int64

We then extract the values we are interested in using [] syntax:

counts[values]   # returns a Series
a 2
b 1
Name: A, dtype: int64

We then use the Series' sum() method:

counts[values].sum()
3

Counting the total number of occurrences

Consider the same df as above:

df = pd.DataFrame({"A":["a","b","a"],"B":["a","a","a"]})
df
A B
0 a a
1 b a
2 a a

Solution

To count the total number of "a" in df:

(df == "a").sum().sum()
5

Explanation

Once again, we first check for the presence of "a" like so:

df == "a"   # returns a Series
A B
0 True True
1 False True
2 True True

True is internally represented as a 1, while False as a 0. Taking the sum of each column yields:

(df == "a").sum()   # returns a Series
A 2
B 3
dtype: int64

This tells us that we have 2 occurrences of "a" in column A, and 3 in B. What we want is the total number so we must take a second sum:

(df == "a").sum().sum()
5
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Published by Isshin Inada
Edited by 0 others
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