Get the First Row of Dataframe Pandas

Get the First Row of a Pandas DataFrame Using
pandas.DataFrame.iloc
Property  Get the First Row From a Pandas DataFrame Based on Specified Condition
This tutorial explains how we can get the first row from a Pandas DataFrame using the pandas.DataFrame.iloc
property and pandas.DataFrame.head()
method.
We will use the DataFrame in the example below to explain how we can get the first row from a Pandas DataFrame.
import pandas as pd
df = pd.DataFrame({
'C_1': ["A","B","C","D"],
'C_2': [40,34,38,45],
'C_3': [430, 980, 200, 350],
})
print(df)
Output:
C_1 C_2 C_3
0 A 40 430
1 B 34 980
2 C 38 200
3 D 45 350
Get the First Row of a Pandas DataFrame Using pandas.DataFrame.iloc
Property
import pandas as pd
df = pd.DataFrame({
'C_1': ["A","B","C","D"],
'C_2': [40,34,38,45],
'C_3': [430, 980, 200, 350],
})
row_1=df.iloc[0]
print("The DataFrame is:")
print(df,"\n")
print("The First Row of the DataFrame is:")
print(row_1)
Output:
The DataFrame is:
C_1 C_2 C_3
0 A 40 430
1 B 34 980
2 C 38 200
3 D 45 350
The First Row of the DataFrame is:
C_1 A
C_2 40
C_3 430
Name: 0, dtype: object
It displays the first row of the DataFrame df
. To select the first row, we use the default index of the first row i.e. 0
with the iloc
property of the DataFrame.
Get the First Row From a Pandas DataFrame Using the pandas.DataFrame.head()
Method
The pandas.DataFrame.head()
method returns a DataFrame with topmost 5 rows of the DataFrame. We can also pass a number as an argument to the pandas.DataFrame.head()
method representing the number of topmost rows to be selected. We can pass 1 as an argument to the pandas.DataFrame.head()
method to only select the first row of the DataFrame.
import pandas as pd
df = pd.DataFrame({
'C_1': ["A","B","C","D"],
'C_2': [40,34,38,45],
'C_3': [430, 980, 200, 350],
})
row_1=df.head(1)
print("The DataFrame is:")
print(df,"\n")
print("The First Row of the DataFrame is:")
print(row_1)
Output:
The DataFrame is:
C_1 C_2 C_3
0 A 40 430
1 B 34 980
2 C 38 200
3 D 45 350
The First Row of the DataFrame is:
C_1 C_2 C_3
0 A 40 430
Get the First Row From a Pandas DataFrame Based on Specified Condition
To extract the first row satisfying specified conditions from a DataFrame, we at first filter the rows satisfying specified conditions and then select the first row from the filtered DataFrame using the methods discussed above.
import pandas as pd
df = pd.DataFrame({
'C_1': ["A","B","C","D"],
'C_2': [40,34,38,45],
'C_3': [430, 980, 500, 350],
})
filtered_df=df[(df.C_2 < 40) & (df.C_3 > 450)]
row_1_filtered=filtered_df.head(1)
print("The DataFrame is:")
print(df,"\n")
print("The Filtered DataFrame is:")
print(filtered_df,"\n")
print("The First Row with C_2 less than 45 and C_3 greater than 450 is:")
print(row_1_filtered)
Output:
The DataFrame is:
C_1 C_2 C_3
0 A 40 430
1 B 34 980
2 C 38 500
3 D 45 350
The Filtered DataFrame is:
C_1 C_2 C_3
1 B 34 980
2 C 38 500
The First Row with C_2 less than 45 and C_3 greater than 450 is:
C_1 C_2 C_3
1 B 34 980
It will display the first row with the value of column C_2
less than 45 and the value of C_3
column greater than 450.
We can also use the query()
method to filter the rows from the DataFrame.
import pandas as pd
df = pd.DataFrame({
'C_1': ["A","B","C","D"],
'C_2': [40,34,38,45],
'C_3': [430, 980, 500, 350],
})
filtered_df=df.query('(C_2 < 40) & (C_3 > 450)')
row_1_filtered=filtered_df.head(1)
print("The DataFrame is:")
print(df,"\n")
print("The Filtered DataFrame is:")
print(filtered_df,"\n")
print("The First Row with C_2 less than 45 and C_3 greater than 450 is:")
print(row_1_filtered)
Output:
The DataFrame is:
C_1 C_2 C_3
0 A 40 430
1 B 34 980
2 C 38 500
3 D 45 350
The Filtered DataFrame is:
C_1 C_2 C_3
1 B 34 980
2 C 38 500
The First Row with C_2 less than 45 and C_3 greater than 450 is:
C_1 C_2 C_3
1 B 34 980
It will filter all the rows with the value of column C_2
less than 45 and the value of C_3
column greater than 450 using the query()
method and then select the first row from the filtered_df
using the head()
method.