Update README.md

README.md

@@ -15,9 +15,8 @@ Data is retrieved from [Corpernicus Climate Data Store](https://cds.climate.cope
 Thailand areas in this context is **Latitude** = **[5.77434, 20.43353]** and **Longitude** = **[97.96852, 105.22908]** <br/>
 For more details of data, you can refer to [ERA5-Land hourly data from 1950 to present](https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-land?tab=overview)
 - Data Granularity: Hourly per Latitude/ Longitude
-- Period: **01/Jan/2010** - **08/May/2023**
-- Temperature Unit: Kelvin
-
+- Period: **31/Dec/1999** - **08/May/2023**
+- Temperature Unit: Celsius (°C) (Original data from [ERA5-Land hourly data from 1950 to present](https://cds.climate.copernicus.eu/cdsapp#!/dataset/10.24381/cds.e2161bac?tab=overview) is Kelvin)
 
 # Source Data
 - Organization of the producer: ECMWF
@@ -53,8 +52,8 @@ for year in year_list:
                 },
         f'{year}_{month}_hourly_2m_temp_TH.grib')
 ```
-Direct file output from API is in ```.grib``` format, to make it easy for futher analysis work, I have converted it to ```.parquet``` format.
-To convert GRIB format to pandas datafram, you can use [xrray](https://github.com/pydata/xarray) and [cfgrib](https://github.com/ecmwf/cfgrib) library to help as below example snippet of code.
+Direct file output from API is in ```.grib``` format, to make it easy for further analysis work, I have converted it to ```.parquet``` format. <br/>
+To convert GRIB format to pandas dataframe, you can use [xrray](https://github.com/pydata/xarray) and [cfgrib](https://github.com/ecmwf/cfgrib) library to help as below example snippet of code.
 
 ``` python
 import xarray as xr
@@ -65,15 +64,18 @@ df = ds.to_dataframe().reset_index()
 
 ```
 
+
+
+
 ## Licensing
 [Climate Data Store Product Licensing](https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf)
 
 ## Citation
 - This data was generated using **Copernicus Climate Change Service** information and <br/>
-contains modified **Copernicus Climate Change Service** information on 2020/Jan/01 - 2023/May/08 data period
+contains modified **Copernicus Climate Change Service** information on 1999/Dec/31 - 2023/May/08 data period
 
 - Muñoz Sabater, J. (2019): ERA5-Land hourly data from 1950 to present. <br/>
-- Copernicus Climate Change Service (C3S) Climate Data Store (CDS). <br/>
+Copernicus Climate Change Service (C3S) Climate Data Store (CDS). <br/>
 DOI: [10.24381/cds.e2161bac](https://cds.climate.copernicus.eu/cdsapp#!/dataset/10.24381/cds.e2161bac?tab=overview) (Accessed on 13-May-2023)
 
 - Copernicus Climate Change Service (C3S) (2022): ERA5-Land hourly data from 1950 to present. <br/>