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We will look at methods for adding a header row to a pandas dataframe, as well as the option to pass in the names directly in the dataframe or by assigning the column names in a list directly to dataframe.columnsthe method.

We will also introduce Pandas's DataFrameto add a header without replacing the current header. In other words, we move the current header down and add it to DataFrameas another record.

We will also look at an example of how to add a header row to a csv file when reading it pandas.dataframe.

Add a header row by passing it directly in the dataframe method

We'll pass directly to using columnsthe argument .headerDataFrame

Consider the following code:

# python 3.x
import pandas as pd
import numpy as np

df = pd.DataFrame(data=np.random.randint(0, 10, (6, 4)), columns=["a", "b", "c", "d"])
print(df)

Output:

   a  b  c  d
0  4  4  4  0
1  8  1  2  5
2  3  0  4  3
3  3  7  2  4
4  8  3  1  8
5  6  7  5  9

dataframe.columnsAdd a header row using

We can also dataframe.columnsadd a header row to the using DataFrame.

Consider the following code:

# python 3.x
import pandas as pd
import numpy as np

df = pd.DataFrame(data=np.random.randint(0, 10, (6, 4)))
df.columns = ["a", "b", "c", "d"]
print(df)

Output:

   a  b  c  d
0  5  2  6  7
1  4  5  9  0
2  8  3  0  4
3  6  3  1  1
4  9  3  4  8
5  7  5  0  6

Add headers without replacing current headers

Another option is to add a header row as an additional level to the column index to make it MultiIndex. This approach is useful when we need an extra layer of information for the columns.

Consider the following code:

# python 3.x
import pandas as pd
import numpy as np

df = pd.DataFrame(data=np.random.randint(0, 10, (6, 4)), columns=["a", "b", "c", "d"])
df.columns = pd.MultiIndex.from_tuples(zip(["A", "B", "C", "D"], df.columns))
print(df)

Output:

   A  B  C  D
   a  b  c  d
0  2  6  4  6
1  5  0  5  1
2  9  6  6  1
3  8  9  7  4
4  6  5  6  6
5  3  9  1  5

When reading a csv file, headeradd rows DataFrameto

read_csvWe can use this directly in names, or if the file has no header, we can set it explicitly header = None.

Consider the following code:

# python 3.x
import pandas as pd
import numpy as np

df = pd.Cov = pd.read_csv("path/to/file.csv", sep="\t", names=["a", "b", "c", "d"])