Data Exploration and Analysis
- Descriptive statistics: Pandas provides functions to compute common summary statistics like mean, median, mode, standard deviation, etc.
- Filtering and slicing: You can filter data based on specific criteria or select subsets of data using various methods.
- Aggregation and grouping: Pandas allows grouping data based on one or more variables and performing aggregations on them.
- Merging and joining: You can combine multiple datasets based on common columns or indices.
- Time series analysis: Pandas has excellent support for working with time series data, including date/time indexing and resampling.
| append() | Adding rows list , dictionary to DataFrame |
| Settings | Managing DataFrame display option values |
| apply | Applying function along an Axis or elements |
| at | Get and Set data using rows and columns |
| astype | Cast to a specified dtype |
| cut | Using segments for categorizing values |
| describe | Descriptive statistics of DataFrame or series |
| groupby | combining data and aggregate functions |
| get_dummies | Convert categorical variable into dummy/indicator variables |
| head | First n rows of the DataFrame |
| isnull | Checking NaN or None data |
| iloc | Values at different position using integer |
| info | Detail information about the Dataframe |
| loc | Values at different position using column label |
| filter | Condition based filtering of rows |
| fillna | Filling NaN data |
| merge | combining DataFrame and aggregate functions |
| methods | Pandas DataFrame methods |
| nlargest | n elements in descending sorted values |
| mask | conditional replacement of data |
| query | Filtering data by using conditions |
| count | Number of rows or columns with different options |
| max | Max value of required axis |
| mean | Mean value of required axis |
| min | Min value of required axis |
| rolling | rolling window calculations |
| shape, size, ndim | Dimensions of the DataFrame |
| std | Standard Deviation on required axis |
| sum | Sum of values of required axis |
| set_index | Creating index using one or more columns |
| sort_values | Sort columns in ascending or descending |
| tolist | From DataFrame to List |
| notnull | Not None and Not Null values checking |
| pivot() | Reshaped data based on column values |
| pivot_table() | Reshaped data with aggregate functions based on column values |
| reset_index | Remove index of the DataFrame |
| value_counts | counts of unique values |
| unique | Unique Data of a column |
| where | Data updating based on condition |
Subhendu Mohapatra
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