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This article demonstrates how to get the indices of rows that match a certain condition in Pandas.

The necessity of finding the index of the rows is important in feature engineering. These skills are useful in removing outliers or abnormal values ​​in a Dataframe. The index, also known as the row labels, can be found in Pandas using several functions. In the following example, we will work with a DataFrame created using the following code snippet.

import pandas as pd
import numpy as np

np.random.seed(0)

df = pd.DataFrame(np.random.randint(1, 20, size=(20, 4)), columns=list("ABCD"))

print(df)

Output:

     A   B   C   D
0   13  16   1   4
1    4   8  10  19
2    5   7  13   2
3    7   8  15  18
4    6  14   9  10
5   17   6  16  16
6    1  19   4  18
7   15   8   1   2
8   10   1  11   4
9   12  19   3   1
10   1   5   6   7
11   9  18  16   5
12  10  11   2   2
13   8  10   4   7
14  12  15  19   1
15  15   4  13  11
16  12   5   7   5
17  16   4  13   5
18   9  15  16   4
19  16  14  17  18

Get the index of rows containing integers/floats in Pandas

pandas.DataFrame.locFunction can access rows and columns by their labels/names. It directly returns the rows matching the given boolean condition passed as label. Note df.locthe square brackets around in the snippet.

import pandas as pd
import numpy as np

np.random.seed(0)

df = pd.DataFrame(np.random.randint(1, 20, size=(20, 4)), columns=list("ABCD"))

print(df.loc[df["B"] == 19])

The rows corresponding to the Boolean condition will be returned in the output in Dataframe format.

Output:

    A   B  C   D
6   1  19  4  18
9  12  19  3   1

Multiple conditions can be chained together and applied together in the function as shown below. This helps to isolate rows based on a specific condition.

import pandas as pd
import numpy as np

np.random.seed(0)

df = pd.DataFrame(np.random.randint(1, 20, size=(20, 4)), columns=list("ABCD"))

print(df.loc[(df["B"] == 19) | (df["C"] == 19)])

Output:

     A   B   C   D
6    1  19   4  18
9   12  19   3   1
14  12  15  19   1

pandas.DataFrame.index()Get the index of the row with

pandas.DataFrame.index()This is the simplest way to implement if you want to find only the matching indices of a DataFrame that satisfy a boolean condition passed as an argument .

import pandas as pd
import numpy as np

np.random.seed(0)

df = pd.DataFrame(np.random.randint(1, 20, size=(20, 4)), columns=list("ABCD"))

print(df.index[df["B"] == 19].tolist())

In the above code snippet, the rows Ain column == 1that match the Boolean condition are returned as output as shown below.

Output:

[6, 9]

The reason we tolist()put index()after the method is to Indexconvert into a list, otherwise, the result is of Int64Indexdata type.

Int64Index([6, 9], dtype='int64'

It is also possible to retrieve only the index based on multiple conditions. This code can be written as follows.

import pandas as pd
import numpy as np

np.random.seed(0)

df = pd.DataFrame(np.random.randint(1, 20, size=(20, 4)), columns=list("ABCD"))

print(df.index[(df["B"] == 19) | (df["C"] == 19)].tolist())

Output:

[6, 9, 14]

Get the index of rows containing a string in Pandas

String values ​​can be matched based on two methods. Both methods shown in the previous section can be used, except the condition changes.

In the following examples, we will use the following snippet.

import pandas as pd

df = pd.DataFrame(
    {
        "Name": ["blue", "delta", "echo", "charlie", "alpha"],
        "Type": ["Raptors", "Raptors", "Raptors", "Raptors", "Tyrannosaurus rex"],
    }
)

print(df)

Output:

      Name               Type
0     blue            Raptors
1    delta            Raptors
2     echo            Raptors
3  charlie            Raptors
4    alpha  Tyrannosaurus rex

Get the index of the row with an exact string match

The equality condition used in the previous section can be used to find exact string matches in a Dataframe. Let's find two strings.

import pandas as pd

df = pd.DataFrame(
    {
        "Name": ["blue", "delta", "echo", "charlie", "alpha"],
        "Type": ["Raptors", "Raptors", "Raptors", "Raptors", "Tyrannosaurus rex"],
    }
)

print(df.index[(df["Name"] == "blue")].tolist())
print("\n")
print(df.loc[df["Name"] == "blue"])
print("\n")
print(df.loc[(df["Name"] == "charlie") & (df["Type"] == "Raptors")])

Output:

[0]

   Name     Type
0  blue  Raptors

      Name     Type
3  charlie  Raptors

As shown above, both the index and the rows that meet the criteria can be received.

Get the index of the row with partial string matching condition

By str.containschaining a DataFrame with a function, you can partially match string values. In the following example, we will search for strings in character and alphaha .

import pandas as pd

df = pd.DataFrame(
    {
        "Name": ["blue", "delta", "echo", "charlie", "alpha"],
        "Type": ["Raptors", "Raptors", "Raptors", "Raptors", "Tyrannosaurus rex"],
    }
)

print(df.index[df["Name"].str.contains("ha")].tolist())
print("\n")
print(df.loc[df["Name"].str.contains("ha")])
print("\n")
print(df.loc[(df["Name"].str.contains("ha")) & (df["Type"].str.contains("Rex"))])

Output:

[3, 4]

      Name               Type
3  charlie            Raptors
4    alpha  Tyrannosaurus rex


    Name               Type
4  alpha  Tyrannosaurus rex

This function is useful for performing partial string matching on multiple columns of a DataFrame.