巴西水文气象是一个开放的时间序列。
hydrobr的Python项目详细描述
氢化橡胶
HydroBr是一个与巴西水文气象时间序列一起工作的开源软件包。在
简介
HydroBr是一个开源软件包，用于在Python中处理巴西水文气象时间序列。这个包裹 提供与巴西国家水务局（Ag encia Nacional deÁguas-ANA）的联系 国家气象研究所（国家气象研究所-INMET）和国家电力系统 运营商（Operador Nacional do Sistema Elétrico-ONS）数据库，帮助用户选择、下载， 对水文气象资料进行预处理和绘图。在
安装
HydroBr的发布版本是0.1.1。在
要安装发布的版本，请使用pip install hydrobr。在
您可以通过克隆
GitHub存储库，并使用安装脚本：
git clone https://github.com/wallissoncarvalho/hydrobr.git
cd hydrobr
python setup.py install
模块-文档
目前，HydroBr包有四个模块：
- 在
get_data-提供与巴西国家水务局连接的功能 巴西国家气象研究所 （国家气象研究所-INMET）和国家电力系统运营商 （Operador Nacional do Sistema Elétrico-ONS）数据库。在
在 - 在
绘图-您将有一些数据绘图选项，例如甘特图（临时数据可用性）图形、流持续时间 并绘制空间站可用性图。在
在 - 在
预处理-提供一个函数，根据日期、数据年数和缺失百分比筛选数据。 此外，还有一个转换数据的函数。在
在 - 在
SaveAs-提供将数据保存到ASCII标准的“.txt”文件中的函数。在
在
将尽快用新功能/方法更新模块。欢迎投稿！在
进口液压br
^{pr2}$来自ANA
help(hydrobr.get_data.ANA)
Help on class ANA in module hydrobr.get_data:
class ANA(builtins.object)
| It provides a connection with the Brazilian National Water Agency (Agência Nacional de Águas - ANA) database
|
| Static methods defined here:
|
| flow_data(list_station, only_consisted=False)
| Get the flow station data series from a list of stations code of the Brazilian National Water Agency
| (ANA) database.
|
| Parameters
| ----------
| list_station : list of strings
| A list of with the stations code as strings.
| only_consisted : boolean, default False
| If True, returns only the data classified as consistent by the provider.
|
| Returns
| -------
| data_stations : pandas DataFrame
| The data os each station as a column in a pandas DataFrame
|
| list_flow_stations(state='', city='', source='ANAF')
| Searches for flow/stage stations registered at the Brazilian National Agency of Water inventory.
|
| Parameters
| ----------
| state : string
| Brazilian state name where the stations are located (e.g., Rio de Janeiro)
| city : string
| Brazilian city name where the stations are located (e.g., Rio de Itaperuna)
| source: string, default 'ANAF'
| The source to look for the data. 'ANA' to get the list of stations from the Brazilian National Water
| Agency (ANA) database, or 'ANAF' to get the filtered list of stations that contain only the stations
| from ANA with registered data.
| More information about ANAF: https://doi.org/10.5281/zenodo.3755065
|
| Returns
| -------
| list_stations : pandas DataFrame
| The selected list of stations as a pandas DataFrame
|
| list_prec_stations(state='', city='', source='ANAF')
| Searches for precipitation stations registered at the Brazilian National Agency of Water (ANA)
|
| Parameters
| ----------
| state : string
| Brazilian state name where the stations are located (e.g., Rio de Janeiro)
| city : string
| Brazilian city name where the stations are located (e.g., Rio de Itaperuna)
| source: string, default 'ANA'
| The source to look for the data. 'ANA' to get the list of stations from the Brazilian National Water
| Agency (ANA) database, or 'ANAF' to get the filtered list of stations that contain only the stations
| from ANA with registered data.
| More information about ANAF: https://doi.org/10.5281/zenodo.3755065
|
| Returns
| -------
| list_stations : pandas DataFrame
| The selected list of stations as a pandas DataFrame
|
| prec_data(list_station, only_consisted=False)
| Get the precipitation station data series from a list of stations code.
|
| Parameters
| ----------
| list_station : list of strings
| A list of with the stations code as strings.
| only_consisted : boolean, default False
| If True, returns only the data classified as consistent by the provider.
|
| Returns
| -------
| data_stations : pandas DataFrame
| The data os each station as a column in a pandas DataFrame
|
| stage_data(list_station, only_consisted=False)
| Get the stage station data series from a list of stations code of the Brazilian National Water Agency
| (ANA) database.
|
| Parameters
| ----------
| list_station : list of strings
| A list of with the stations code as strings.
| only_consisted : boolean, default False
| If True, returns only the data classified as consistent by the provider.
|
| Returns
| -------
| data_stations : pandas DataFrame
| The data os each station as a column in a pandas DataFrame
|
| ----------------------------------------------------------------------
来自INMET
help(hydrobr.get_data.INMET)
Help on class INMET in module hydrobr.get_data:
class INMET(builtins.object)
| It provides a connection with the Brazilian National Institute of Meteorology (Instituto Nacional de
| Meteorologia - INMET) database.
|
| Static methods defined here:
|
| daily_data(station_code, filter=True)
| Searches for all the data of a station registered at the Brazilian National Institute of Meteorology
| (Instituto Nacional de Meteorologia - INMET) database.
|
| Returns a pandas daily DataFrame with six variables for each day:
| - Prec - Precipitation (mm)
| - Tmean - Daily mean Temperature (ºC)
| - Tmax - Maximum Temperature (ºC)
| - Tmin - Minimum Temperature (ºC)
| - RH - Relative Humidity (%)
| - SD - Sunshine Duration (hours)
|
| Parameters
| ----------
| station_code : string
| Code of the station as a string
| filter: boolean, default True
| There is stations with repeated registered data. If 'True' the function returns a panda DataFrame
| with the first occurrence of the date. If 'False' return a pandas DataFrame with, in some cases,
| repeated datetime index.
|
| Returns
| -------
| data : pandas DataFrame
| The data of the selected station as a pandas DataFrame
|
| hourly_data(station_code)
| Searches for all the data of a station registered at the Brazilian National Institute of Meteorology
| (Instituto Nacional de Meteorologia - INMET) database.
|
| Only works for Automatic Stations.
|
| Returns a pandas hourly DataFrame with 17 variables for each day:
| - Tins - Instant Temperature (ºC)
| - Tmax - Maximum Temperature (ºC)
| - Tmin - Minimum Temperature (ºC)
| - RHins - Instant Relative Humidity (%)
| - RHmax - Maximum Relative Humidity (%)
| - RHmin - Minimum Relative Humidity (%)
| - DPins - Instant Dew Point Temperature (ºC)
| - DPmax - Maximum Dew Point Temperature (ºC)
| - DPmin - Minimum Dew Point Temperature (ºC)
| - Pins - Instant Pressure (hPa)
| - Pmax - Maximum Pressure (hPa)
| - Pmin - Minimum Pressure (hPa)
| - Wspeed - Wind Speed (m/s)
| - Wdir - Wind direction (º)
| - Wgust - Wind gust (m/s)
| - Rad - Global Radiation (kJ/m²)
| - Prec - Precipitation (mm)
|
| Parameters
| ----------
| station_code : string
| Code of the station as a string.
|
| Returns
| -------
| data : pandas DataFrame
| The data of the selected station as a pandas DataFrame.
|
| list_stations(station_type='both')
| Searches for precipitation stations registered at the Brazilian National Agency of Water (ANA) or the INMET
| inventory.
|
| Parameters
| ----------
| station_type : string, default 'both'
| The type of station. 'both' to get the list of automatic and manual gauge stations, 'automatic' to get only
| the automatic gauge stations, and 'conventional' to get only the conventional gauge stations.
| Returns
| -------
| list_stations : pandas DataFrame
| The selected list of stations as a pandas DataFrame
|
| ----------------------------------------------------------------------
来自国家统计局的数据
help(hydrobr.get_data.ONS)
Help on class ONS in module hydrobr.get_data:
class ONS(builtins.object)
| Provide data from the National Electric System Operator (Operador Nacional do Sistema Elétrico - ONS) database.
|
| Static methods defined here:
|
| daily_data()
| Returns all the naturalized daily flow data of different reservoirs from the National Electric System
| Operator (Operador Nacional do Sistema Elétrico - ONS) database.
|
| Parameters
| ----------
|
| Returns
| -------
| data : pandas DataFrame
| All the naturalized daily flow data as a pandas DataFrame, where each column refers to a specific
| reservoir.
| ----------------------------------------------------------------------
预处理方法
help(hydrobr.PreProcessing)
Help on class PreProcessing in module hydrobr.preprocessing:
class PreProcessing(builtins.object)
| Static methods defined here:
|
| daily_to_monthly(data, method='sum')
| Transform a time series of daily data into a time series monthly data.
|
| In the conversion process a month with a day missing data is considered as a missing month.
|
| Parameters
| ----------
| data : pandas DataFrame
| A Pandas daily DataFrame with DatetimeIndex where each column corresponds to a station.
| method: str, default sum
| The method used to convert. If 'sum', the monthly data will be the sum of the daily data. If 'mean', the
| monthly data will be the mean of the daily data.
|
| Returns
| -------
| monthly_data : pandas DataFrame
| The monthly pandas DataFrame
|
| stations_filter(data, n_years=10, missing_percentage=5, start_date=False, end_date=False)
| A composed method to filter stations.
|
| First, the method filters the stations data by the Start Date and the End Date, it its passed. After that,
| the is selected only the stations with at least a defined number of years between the first date and the
| last date of the station. At the end is selected the stations that contains at least one window of data with
| the number of years and a maximum missing data percentage.
|
| Parameters
| ----------
| data : pandas DataFrame
| A Pandas daily DataFrame with DatetimeIndex where each column corresponds to a station.
| n_years: int, default 10
| The minimum number of years of registered data for the station between the first date and the end date.
| missing_percentage: int, default 5
| The maximum missing data percentage in a window with n_years.
| A number between 0 and 100
| start_date : int, float, str, default False
| The desired start date for the output DataFrame.
| See: pandas.to_datetime documentation if have doubts about the date format
| end_date: int, float, str, default False
| The desired end date for the output DataFrame.
| See: pandas.to_datetime documentation if have doubts about the date format
|
| Returns
| -------
| data : pandas DataFrame
| A pandas DataFrame with only the filtered stations
|
| ----------------------------------------------------------------------
绘图方法
help(hydrobr.Plot)
Help on class Plot in module hydrobr.graphics:
class Plot(builtins.object)
| Static methods defined here:
|
| fdc(data, y_log_scale=True)
| Make a flow duration curve plot.
|
| Parameters
| ----------
| data : pandas DataFrame
| A Pandas daily DataFrame with DatetimeIndex where each column corresponds to a station..
| y_log_scale : boolean, default True
| Defines if the the plotting y-axis will be in the logarithmic scale.
|
| Returns
| -------
| fig : plotly Figure
|
| gantt(data, monthly=True)
| Make a Gantt plot, which shows the temporal data availability for each station.
|
| Parameters
| ----------
| data : pandas DataFrame
| A Pandas daily DataFrame with DatetimeIndex where each column corresponds to a station..
| monthly : boolean, default True
| Defines if the availability count of the data will be monthly to obtain a more fluid graph.
|
| Returns
| -------
| fig : plotly Figure
|
| spatial_stations(list_stations, mapbox_access_token)
| Make a spatial plot of the stations.
|
| Parameters
| ----------
| list_stations : pandas DataFrame
| A Pandas DataFrame that must contain Latitude, Longitude, Name, and Code columns.
| mapbox_access_token : str
| Mapbox access toke, which can be obtained at https://account.mapbox.com/access-tokens/
|
| Returns
| -------
| fig : plotly Figure
|
| ----------------------------------------------------------------------
SaveAs方法
help(hydrobr.SaveAs)
Help on class SaveAs in module hydrobr.save:
class SaveAs(builtins.object)
| Static methods defined here:
|
| asc_daily_flow(data, path_save)
| Save each column of the flow stations DataFrame into a ".txt" file in the ASCII standard.
|
| Parameters
| ----------
| data : pandas DataFrame
| A Pandas daily DataFrame with DatetimeIndex where each column corresponds to a station.
| path_save: string
| The computer location where the ".txt" files will be saved.
|
| Returns
| -------
| Saved data in the path_save
|
| asc_daily_prec(data, path_save)
| Save each column of the precipitation stations DataFrame into a ".txt" file in the ASCII standard.
|
| Parameters
| ----------
| data : pandas DataFrame
| A Pandas daily DataFrame with DatetimeIndex where each column corresponds to a station.
| path_save: string
| The computer location where the ".txt" files will be saved.
|
| Returns
| -------
| Saved data in the path_save
| ----------------------------------------------------------------------
模块
我的博客上的HydroBr页面上提供了使用示例。在
依赖关系
许可证
如何引证
瓦利森·莫雷拉·德卡瓦略。（2020年7月5日）。HydroBr：一个Python包，用于巴西水文气象时间 系列。（版本0.1.1）。泽诺多。http://doi.org/10.5281/zenodo.3931027
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