Read CSV Read csv with Python. If header=None , column names are assigned as integer indices and first line of the file is read as first row of the DataFrame: df = pd.read_csv("SampleDataset.csv", header=None) df.head() pandas.read_csv ¶ pandas.read_csv ... Row number(s) to use as the column names, and the start of the data. We will pass the first parameter as the CSV file and the second parameter the list of specific columns in the keyword usecols.It will return the data of the CSV file of specific columns. Get DataFrame Column Names. You can export a file into a csv file in any modern office suite including Google Sheets. ... index_col – This defines the names of row labels, it can be a column from the data or the list of integer or string, None by default. : Sell) or using their column index (Ex. Use the following csv data as an example. When you want to only pull in a limited amount of columns, usecols is the function for you. Let’s see how to read it into a DataFrame using Pandas read_csv() function. DataFrame.columns. This can be done with the help of the pandas.read_csv() method. We will use Pandas coliumns function get the names of the columns. import pandas emp_df = pandas.read_csv('employees.csv') print(emp_df) Output: Emp ID Emp Name Emp Role 0 1 Pankaj Kumar Admin 1 2 David Lee Editor 2 3 Lisa Ray Author You can access the column names of DataFrame using columns property. Pandas returns the names of columns as Pandas Index object. It is the basic object storing axis labels. Let us see how to read specific columns of a CSV file using Pandas. Example 1: Print DataFrame Column Names. In this example, we get the dataframe column names and print them. In this post, we will first see how to extract the names of columns from a dataframe. The pandas read_csv() function is used to read a CSV file into a dataframe. df = pd.read_csv(file_name, usecols = [0,1,2]) How to read csv files in python using pandas? You have two options on how you can pull in the columns – either through a list of their names (Ex. To get the names of the data frame rows: >>> df.index Index(['Alice', 'Bob', 'Emma'], dtype='object') Get the row names of a pandas data frame (Exemple 2) Another example using the csv file train.csv (that can be downloaded on kaggle): >>> import pandas as pd >>> df = pd.read_csv('train.csv') >>> df.index RangeIndex(start=0, stop=1460, step=1) Python Program pd.read_csv(file_name, index_col= 0) usecols. Read CSV file in Pandas as Data Frame pandas read_csv method of pandas will read the data from a comma-separated values file having .csv as a pandas data-frame. It returns an object. Here are two approaches to get a list of all the column names in Pandas DataFrame: First approach: my_list = list(df) Second approach: my_list = df.columns.values.tolist() Later you’ll also see which approach is the fastest to use. The pandas function read_csv() reads in values, where the delimiter is a comma character. Therefore, if no column names are specified, default behavior of csv file is to take header=0 and column names are inferred from the ,first line of the file. Automatically clean pandas dataframe column names: R. Burke Squires: NIAID Bioinformatics and Computational Biosciences Branch: OK, let's get started by importing the pandas library. The following is the general syntax for loading a csv file to a dataframe: import pandas as pd df = pd.read_csv(path_to_file) The Example. Now for the second code, I took advantage of some of the parameters available for pandas.read_csv() header & names. You can access the column names using index. Related course: Data Analysis with Python Pandas. : 0). It comes with a number of different parameters to customize how you’d like to read the file. However, having the column names as a list is useful in many situation.