Email and websites are two important mediums of customer communication in recent times. Technically, email and website-based communications rely on some specific uniform resource locator (URL) addresses. However, this type of business communication suffers from the risk of cyberattack via uniform resource locator phishing. Hence, phishing uniform resource locator detection is necessary for secure customer communication. One of the prime drawbacks in traditional approaches relates to the detection and removal of constant and null values associated with uniform resource locators. Intruders often target and manipulate these constant and null values to make legitimate URLs into phished ones. This paper proposes a new method of phishing uniform resource locator detection with exploratory data analysis. The exploratory data analysis technique efficiently identifies and removes constant and null values from the uniform resource locator structures. The proposed method considers thirty uniform resource locator features for classifying legitimate and phishing emails and websites. The performance of the proposed method shows 92.30% classification accuracy.