Pandas – Select Rows with non empty strings in a Column

This tutorial will discuss about different ways to select DataFrame rows with non empty strings in a column in Pandas.

Table Of Contents

Preparing DataSet

Let’s create a DataFrame with some dummy data.

import pandas as pd

data = {'Col_A': ["11", "12", "13", "14", "15", "16", "17"],
        'Col_B': ["21", "22", "    ", "24", "   ", "26", "   "],
        'Col_C': ["33", "32", "33", "35", "35", "36", "35"]}

index = ['X1', 'X2', 'X3', 'X4', 'X5', 'X6', 'X7']

# Create a DataFrame from a dictionary
df = pd.DataFrame.from_dict(data)

# Set the index list as Index of DataFrame
df.set_index(pd.Index(index), inplace=True)

print (df)

Output

   Col_A Col_B Col_C
X1    11    21    33
X2    12    22    32
X3    13          33
X4    14    24    35
X5    15          35
X6    16    26    36
X7    17          35

Now we will operate on this DataFrame.

Select DataFrame Rows with non empty values in a Column

We can use the loc[] attribute of a DataFrame, to select only those rows from a DataFrame which contains a non empty string in a specified column.

For that first we will select a particular column and then we will strip all string values in that column, i.e. to remove the leading and trailing spaces from each value in that column. Then we will check if any value in that particular column is empty or not. For that, we will apply a condition on that column and it will return as a boolean series.

A True value in this boolean series represents that the corresponding value in that particular column is not empty. Then we will pass this boolean series into the loc[] attribute of DataFrame. It will return a DataFrame containing only those rows from the original DataFrame, which contains the not empty value in the specified column. let’s see the complete example, in which we will select roes from DataFramw where column Col_B has non empty values.

# Select Rows from DataFrame where values in
# Column “Col_B" are not empty
subDf = df.loc[df['Col_B'].str.strip() != ""]

print(subDf)

Output

   Col_A Col_B Col_C
X1    11    21    33
X2    12    22    32
X4    14    24    35
X6    16    26    36

Summary

We learned about different ways to select DataFrame rows with non empty strings in a speficied Column in Pandas.