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EDA & Statistics Practice with Pandas
Build a disciplined exploratory workflow with grouped descriptive statistics, quantiles, IQR-based anomaly detection, correlations, and distribution summaries. Each problem requires a reproducible DataFrame result rather than an informal notebook observation.
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Python Problems
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45 problems0 Easy(0%)
15 Medium(33%)
30 Hard(67%)
0 Expert(0%)
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43 skillsadtechaggbankingcomputed columncorrelationdata bucketingdescribedescriptive statisticsdescriptive statsdistribution analysiseda statisticsfillnafilteringfintechfood deliverygroupbyhealthcarelodginglogisticsmergemobilitymulti step pipelinenamed aggnp selectnp wherenumeric thresholdoutlier detectionpaymentspearsonrpercentilequantilerankreal estateretailsaasscipy statssingle tablesocialstreamingtelecomthree tabletransformtwo table
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