Merge pull request #54 from cparmet/readme-inconsistency

Docs: Be consistent with colon vs dash after method name

Author: cparmet

README.md

@@ -117,20 +117,20 @@ Standard Pandas methods:
 - `.check.value_counts()` - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.value_counts) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.value_counts)
 
 New methods in Pandas Checks:
-- `.check.function()`: Apply an arbitrary lambda function to your data and see the result - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.function) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.function)
-- `.check.ncols()`: Count columns - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.ncols) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.ncols)
-- `.check.ndups()`: Count rows with duplicate values - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.ndups) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.ndups)
-- `.check.nnulls()`: Count rows with null values - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.nnulls) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.nnulls)
-- `.check.nrows()`: Count rows - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.nrows) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.nrows)
-- `.check.print()`: Print a string, a variable, or the current dataframe - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.print) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.print)
+- `.check.function()` - Apply an arbitrary lambda function to your data and see the result - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.function) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.function)
+- `.check.ncols()` - Count columns - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.ncols) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.ncols)
+- `.check.ndups()` - Count rows with duplicate values - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.ndups) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.ndups)
+- `.check.nnulls()` - Count rows with null values - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.nnulls) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.nnulls)
+- `.check.nrows()` - Count rows - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.nrows) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.nrows)
+- `.check.print()` - Print a string, a variable, or the current dataframe - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.print) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.print)
 
 ### Export interim files
-- `.check.write()`: Export the current data, inferring file format from the name - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.write) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.write)
+- `.check.write()` - Export the current data, inferring file format from the name - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.write) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.write)
 
 ### Time your code
-- `.check.print_time_elapsed(start_time)`: Print the execution time since you called `start_time = pdc.start_timer()` - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.print_time_elapsed) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.print_time_elapsed)
+- `.check.print_time_elapsed(start_time)` - Print the execution time since you called `start_time = pdc.start_timer()` - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.print_time_elapsed) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.print_time_elapsed)
 <br></br>
-> 💡 Tip:  You can also use this stopwatch outside a method chain, anywhere in your Python code:  
+> 💡 Tip:  You can also use this stopwatch outside a method chain, anywhere in your Python code -  
 
 ```python
 from pandas_checks import print_elapsed_time, start_timer
@@ -142,12 +142,12 @@ print_elapsed_time(start_time)
         
 ### Turn Pandas Checks on or off
 These methods can be used to disable subsequent Pandas Checks methods, either temporarily for a single method chain or permanently such as in a production environment.
-- `.check.disable_checks()`: Don't run checks. By default, still runs assertions. - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.disable_checks) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.disable_checks)
-- `.check.enable_checks()`: Run checks again. - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.enable_checks) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.enable_checks)
+- `.check.disable_checks()` - Don't run checks. By default, still runs assertions. - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.disable_checks) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.disable_checks)
+- `.check.enable_checks()` - Run checks again. - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.enable_checks) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.enable_checks)
 
 ### Validate data
 Custom:
-- `.check.assert_data()`: Check that data passes an arbitrary condition - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.assert_data) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.assert_data)
+- `.check.assert_data()` - Check that data passes an arbitrary condition - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.assert_data) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.assert_data)
 
 Types:
 - `.check.assert_datetime()` - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.assert_datetime) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.assert_datetime)
@@ -165,12 +165,12 @@ Values:
 - `.check.assert_no_nulls()` - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.assert_no_nulls) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.assert_no_nulls)
 - `.check.assert_nrows()` - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.assert_nrows) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.assert_nrows)
 - `.check.assert_positive()` - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.assert_positive) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.assert_positive)
-- `.check.assert_same_nrows()`: Check that DataFrame/Series has same number of rows as another DF/Series, for example to validate 1:1 joins - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.assert_same_nrows) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.assert_same_nrows)
+- `.check.assert_same_nrows()` - Check that DataFrame/Series has same number of rows as another DF/Series, for example to validate 1:1 joins - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.assert_same_nrows) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.assert_same_nrows)
 - `.check.assert_unique()` - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.assert_unique) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.assert_unique)
 
 ### Visualize data
-- `.check.hist()`: A histogram - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.hist) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.hist)
-- `.check.plot()`: An arbitrary plot you can customize - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.plot) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.plot)
+- `.check.hist()` - A histogram - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.hist) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.hist)
+- `.check.plot()` - An arbitrary plot you can customize - [DataFrame](https://cparmet.github.io/pandas-checks/API%20reference/DataFrameChecks/#pandas_checks.DataFrameChecks.DataFrameChecks.plot) | [Series](https://cparmet.github.io/pandas-checks/API%20reference/SeriesChecks/#pandas_checks.SeriesChecks.SeriesChecks.plot)
 
 ## Customizing a check