Pandas

README.md

@@ -3220,18 +3220,40 @@ a 1 2
 b 3 4
 ```
 
+```python
+x_col = [1, 3]
+y_col = [2, 4]
+<DF> = pd.DataFrame({'x': x_col, 'y': y_cal}, index=['a', 'b'])
+<DF>.columns # Get the column names: {x, y}
+<DF>.index # Get the index values: {a, b}
+```
+
 ```python
 <DF> = pd.DataFrame(<list_of_rows>) # Rows can be either lists, dicts or series.
 <DF> = pd.DataFrame(<dict_of_columns>) # Columns can be either lists, dicts or series.
 ```
 
+Descriptive information about dataframe:
+```python
+<DF>.head(n=5) # Return first n occurrences
+<DF>.dtypes # Return data types of each columns
+<DF>.isna/isnull() # Return empty values in <DF>
+<DF>.describe() # Get statistical description of <DF> (both numeric & object)
+```
+
+For selection of multiple elements:
 ```python
 <el> = <DF>.loc[row_key, column_key] # Or: <DF>.iloc[row_index, column_index]
 <Sr/DF> = <DF>.loc[row_key/s] # Or: <DF>.iloc[row_index/es]
 <Sr/DF> = <DF>.loc[:, column_key/s] # Or: <DF>.iloc[:, column_index/es]
 <DF> = <DF>.loc[row_bools, column_bools] # Or: <DF>.iloc[row_bools, column_bools]
 ```
 
+For selection of single element:
+```python
+<el> = <DF>.at[row_index, column_key]
+```
+
 ```python
 <Sr/DF> = <DF>[column_key/s] # Or: <DF>.column_key
 <DF> = <DF>[row_bools] # Keeps rows as specified by bools.
@@ -3249,6 +3271,7 @@ b 3 4
 <DF> = <DF>.sort_index(ascending=True) # Sorts rows by row keys. Use `axis=1` for cols.
 <DF> = <DF>.sort_values(column_key/s) # Sorts rows by the passed column/s. Same.
 ```
+Those methods have optional parameter *inplace*, which would make the changes in the object from they are called and return None.
 
 #### DataFrame — Merge, Join, Concat:
 ```python