IMPORTING CSV IN PANDAS

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In this tutorial, we will learn about Importing CSV module in Python Pandas. We will learn about how to import and work with the csv files.

Python is the best choice for performing data analysis mainly because of amazing availability and integration of pandas. Pandas is a complete package that can help you import and read data much faster and easier by using a CSV file.

importing-csv-in-pandas

We can import csv (comma separated values) files by using a method in pandas known as read_csv. We need to import csv files because sometimes we might have to work with big size datasets for analysis. So, a common format of containing all that data is CSV.

The Syntax for read_csv is:

pd.read_csv(filepath_or_buffer, sep=’, ‘, delimiter=None, header=’infer’, names=None, index_col=None, usecols=None, squeeze=False, prefix=None, mangle_dupe_cols=True, dtype=None, engine=None, converters=None, true_values=None, false_values=None, skipinitialspace=False, skiprows=None, nrows=None, na_values=None, keep_default_na=True, na_filter=True, verbose=False, skip_blank_lines=True, parse_dates=False, infer_datetime_format=False, keep_date_col=False, date_parser=None, dayfirst=False, iterator=False, chunksize=None, compression=’infer’, thousands=None, decimal=b’.’, lineterminator=None, quotechar=’”‘, quoting=0, escapechar=None, comment=None, encoding=None, dialect=None, tupleize_cols=None, error_bad_lines=True, warn_bad_lines=True, skipfooter=0, doublequote=True, delim_whitespace=False, low_memory=True, memory_map=False, float_precision=None)



Step 1: Make Sure You Know The Filepath

The first important step of importing csv in pandas is to know where the csv file is stored. It can store on your personal computer or it can be available on the internet in the form of a url with an extension of ‘.csv’. For example on pc, it might be stored as:

C:\Users\Me\Desktop\filename.csv

Firstly, capture the full path where your CSV file is stored. In my case, the CSV file is stored under the following path:

C:\Users\Ron\Desktop\Clients.csv

Step 2: Apply Code to Import CSV in Pandas

Import pandas in your project and use the read_csv function to import the file in a dataframe. We have used a sample file to read from that you can download from here.

import pandas as pd
df = pd.read_csv ('filename.csv')
df

Importing CSV data

Other Steps: You Can Choose Your Own Columns

Now let’s say that you want to select a bunch of columns of your own choice within your CSV file when you import it. Let’s say that in the sample file we are using; we only need 3 columns for data analysis. We can achieve that by using the column attribute. Now what if you want to select a subset of columns from the CSV file?

import pandas as pd
data = pd.read_csv ('filename.csv')
df = pd.DataFrame(data, columns= ['Region','Country', 'Total Profit'])
df

Importing CSV

You can apply the head() function as well in order to print the first 5 rows of your dataset from the csv file.

import pandas as pd
data = pd.read_csv ('filename.csv')
data.head()

Pandas Head Function

References:



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