如何将np.int64转换为PandasSeries的python int64?

问题描述

我尝试将pandas DataFrame中的数据插入PostgreSQL表中，

I try to insert data from pandas DataFrame into the PostgreSQL table,

表如下:

city_id date        forecast
5       29.05.2019  0
1       29.05.2019  0
151     29.05.2019  0
55      29.05.2019  0
...

类型:

• city_id-numpy.int64
• date-datetime.date
• forecast-numpy.int64

• city_id - numpy.int64
• date - datetime.date
• forecast - numpy.int64

以及将数据插入db的代码块:

And the block of code, that inserting data to db:

        with psycopg2.connect(f"host='{hostname}' \
                              dbname='{database}' \
                              user='{username}' \
                              password='{password}'") as connection:
            with connection.cursor() as cursor:
                connection.set_client_encoding('UTF8')
                for i in df_with_new_one.index:
                    date = df_with_new_one['date'][i]
                    city_id = df_with_new_one['city_id'][i]
                    value = df_with_new_one['forecast'][i]

                    cursor.execute("INSERT INTO forecast \
                    (city_id, computed_time, date, value) \
                    VALUES (%s, %s, %s, %s)", (city_id, now, date, value)) 

其中now被保存为datetime.datetime.now()

然后我得到 ProgrammingError :

    ProgrammingError: can't adapt type 'numpy.int64'

我检查了类型 type(df_with_new_one['forecast'][0])类型是numpy.int64

所以我发现PostreSQL只能读取pythonic int和float，而我尝试的第一件事是使用以下命令将np.int64转换为简单的int:

So I get that PostreSQL can read only pythonic int and float, and the first thing i've tried was converting np.int64 into simple int with:

• tolist()
• pd.to_numeric()
• int()为((int(city_id), now, date, int(value))
• .astype(int)
• .value.astype('int')

• tolist()
• pd.to_numeric()
• int() for ((int(city_id), now, date, int(value))
• .astype(int)
• .value.astype('int')

更新.

• city_id = int(df_with_new_one['city_id'][i])value = int(df_with_new_one['forecast'][i])

不幸的是，它们都不对我有用

当我尝试int()时，出现另一个错误:

When I tried int() I get another error:

    TypeError: cannot convert the series to <class 'int'>

我发现的答案，但没有人帮助我

• psycopg2:无法采用类型'numpy.int64'
• ProgrammingError:(psycopg2.ProgrammingError)无法适应类型' numpy.ndarray'
• Python TypeError:无法将系列转换为< class'int'>尝试在数据框上进行数学运算时
• Python熊猫过滤; TypeError:无法将系列转换为< class'int'>

• psycopg2: can't adapt type 'numpy.int64'
• ProgrammingError: (psycopg2.ProgrammingError) can't adapt type 'numpy.ndarray'
• Python TypeError: cannot convert the series to <class 'int'> when trying to do math on dataframe
• Python Pandas filtering; TypeError: cannot convert the series to <class 'int'>

是否有任何其他方法来更改值的类型?

Are there any other methods to change type of values?

推荐答案

问题出在错误的索引编制中:

The problem was in wrong indexation:

• 第一个索引是从83到1161，在1161之后应该是1161，之后又是83，下一个值是83 + 1，等等.

因此，问题已由.reset_index()

df_with_new_one.reset_index(drop = True, inplace = True)

谢谢大家的回答！

这篇关于如何将np.int64转换为PandasSeries的python int64?的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！