| S.No |
Topic |
Sub-Topics |
| 1 | Pandas | Overview, Installation, Series, DataFrame, Basic operations |
| 2 | Series Basics | Creating Series, Indexing, Slicing, Series methods, Data types |
| 3 | DataFrame Basics | Create DataFrame, Index/Columns, Shape, dtypes, head/tail |
| 4 | Data Selection | loc, iloc, ix, column selection, row selection |
| 5 | Data Filtering | Boolean indexing, conditions, isin, between, query() |
| 6 | Missing Data | isnull, notnull, fillna, dropna, interpolation |
| 7 | Data Cleaning | Duplicates, rename, replace, strip whitespaces, type conversion |
| 8 | Data Transformation | apply, map, applymap, lambda functions, vectorized operations |
| 9 | Aggregation & Grouping | groupby, aggregate, transform, filter, pivot tables |
| 10 | Sorting & Ranking | sort_values, sort_index, rank, ascending/descending, multi-level sorting |
| 11 | Indexing & MultiIndex | set_index, reset_index, hierarchical index, slicing, cross-section |
| 12 | Concatenation & Merging | concat, append, merge, join, indicator |
| 13 | Reshaping Data | melt, pivot, stack, unstack, wide to long format |
| 14 | Time Series Basics | Datetime conversion, date_range, indexing, resampling, frequency |
| 15 | Time Series Advanced | rolling, expanding, shifting, lag/lead, moving average |
| 16 | String Operations | str methods, contains, replace, split, regex |
| 17 | Visualization with Pandas | plot, line, bar, histogram, scatter |
| 18 | Reading/Writing Data | read_csv, read_excel, read_json, to_csv, to_excel |
| 19 | Advanced I/O | read_sql, read_parquet, read_hdf, read_pickle, compression |
| 20 | Exploratory Data Analysis | describe, info, value_counts, correlation, unique |
| 21 | Multi-Column Operations | arithmetic, apply, assign, lambda, broadcasting |
| 22 | Window Functions | rolling, expanding, ewm, groupby with window, custom functions |
| 23 | Categorical Data | category dtype, conversion, codes, sorting, filtering |
| 24 | Sampling & Subsetting | sample, head/tail, nth, slicing, random sampling |
| 25 | Performance Optimization | vectorization, eval/query, categorical, chunking, memory usage |
| 26 | MultiIndex Advanced | stack/unstack, xs, swaplevel, sortlevel, indexing tricks |
| 27 | Custom Functions | apply, pipe, lambda, function chaining, reusable utilities |
| 28 | Integration with NumPy & SciPy | array operations, broadcasting, linear algebra, statistical functions, interoperability |
| 29 | Real World Data Projects | EDA, cleaning, aggregation, visualization, export results |
| 30 | End-to-End Project | Data collection, cleaning, analysis, feature engineering, visualization |
