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In the past three years, covid-19 viruses have spread rapidly worldwide, while low and middle-income countries were affected mostly so far. Emergency limits were imposed due to the rapid infection and significant mortality rates. Only emergency medical treatments are available during these shutdowns and lockdowns in India. All non-emergency treatments, such as Breast Cancer Screening Program (BCSP), have been temporarily halted due to the huge number of deaths caused by coronavirus. However, the ability of BC screening programs to improve survival rates while lowering mortality rates has been well demonstrated. Suspension may result in poorer outcomes for patients with BC. In this regard, early detection and treatment are critical for increased survival and long-term quality of life. Thus, we have taken breast cancer patients' data for the last six years i.e. from 2016 to 2021 in India to properly evaluate and analyze for our research. Assessing recent results for various features from, modeled evaluations can aid pandemic responses. Besides that, we proposed a novel method that implements the EDA technique to graphically represent BC patients' data. This experiment was done using Python programming language on Jupyter 6.4.3 platform. We found the sudden rise of BC patients from lakhs to millions in 2019. This signifies the deadly coronavirus has greatly affected people during the pandemic days when people are more serious about this virus rather than screening their breasts.
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