我将数据从 csv 加载到 Python Pandas 并尝试使列成行(具有重复日期)
I load a data from csv to Python Pandas and try to make the columns to row (with duplicates dates)
:
我使用 Pandas Dataframe 在 python 中加载数据。
我的问题是:我试图将日期的列设为行,将“Country/Region”列设为列。
url_confirmed = 'https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv'
df = pd.read_csv(url_confirmed)
df = df.drop(columns=['Province/State','Lat','Long'],axis=1)
df_piv = pd.melt(df,id_vars=['Country/Region'],var_name='Date',value_name="Value")
我到了这里,真的不知道如何进行
我的最终数据框应该是这样的:
Date Afghanistan Albania and so on
0 1/22/20 0 val
1 1/23/20 300 val
3 1/24/20 4023 val
6 1/25/20 300 val
7 1/26/20 2000 val
8 .. ..
.
.
**非常感谢**
我认为重命名列的简单转置应该可以做到:
url_confirmed = 'https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv'
df = pd.read_csv(url_confirmed)
df = df.drop(columns=['Province/State','Lat','Long'],axis=1)
df = df.T.reset_index() # Transpose and reset index
df.columns = df.iloc[0] # Set first row as header
df = df[1:]
df.rename(columns = {'Country/Region' : 'Date'}, inplace=True)
:
我使用 Pandas Dataframe 在 python 中加载数据。
我的问题是:我试图将日期的列设为行,将“Country/Region”列设为列。
url_confirmed = 'https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv'
df = pd.read_csv(url_confirmed)
df = df.drop(columns=['Province/State','Lat','Long'],axis=1)
df_piv = pd.melt(df,id_vars=['Country/Region'],var_name='Date',value_name="Value")
我到了这里,真的不知道如何进行
我的最终数据框应该是这样的:
Date Afghanistan Albania and so on
0 1/22/20 0 val
1 1/23/20 300 val
3 1/24/20 4023 val
6 1/25/20 300 val
7 1/26/20 2000 val
8 .. ..
.
.
**非常感谢**
我认为重命名列的简单转置应该可以做到:
url_confirmed = 'https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv'
df = pd.read_csv(url_confirmed)
df = df.drop(columns=['Province/State','Lat','Long'],axis=1)
df = df.T.reset_index() # Transpose and reset index
df.columns = df.iloc[0] # Set first row as header
df = df[1:]
df.rename(columns = {'Country/Region' : 'Date'}, inplace=True)