Question

我该怎么做才能防止pandas将我的字符串值转换为float。列library(ggplot2) ggplot(data_tidy, aes(x = reorder(player, -value), y = value, col = this_player, fill = this_player)) + geom_bar(stat = "identity") + facet_grid(statcategory ~ statistic) + theme(axis.title.x=element_blank(), axis.text.x=element_blank(), axis.ticks.x=element_blank(), axis.title.y=element_blank()) + ggtitle("Feet / Minute Players are Running") + theme(plot.title = element_text(lineheight=.8, face="bold", hjust = 0.5))和Billing Doc.包含10-11位数字，这些数字将存储在MySQL表中，其数据类型为CHAR（15）。当我执行以下脚本时，我会在每个数字的末尾看到Sales Order。我想在我们的数据库中将它们视为字符串/字符。 .0字段包含Billing Doc.等数字，其存储在数据库中为3206790137, 3209056079, 3209763880, 3209763885, 3206790137。数据库中“结算”文档的列数据类型为3206790137.0, 3209056079.0, 3209763880.0, 3209763885.0, 3206790137.0。

CHAR(15)

当我创建一个简单的df并打印它时，问题就不会出现了。

def insert_billing(df):
        df = df.where((pd.notnull(df)), None)
        for row in df.to_dict(orient="records"):
            bill_item = row['Bill.Item']
            bill_qty = row['Billed Qty']
            bill_doct_date = row['Billi.Doc.Date']
            bill_doc = row['Billing Doc.']
            bill_net_value = row['Billi.Net Value']
            sales_order = row['Sales Order']
            import_date = DT.datetime.now().strftime('%Y-%m-%d')


            query = "INSERT INTO sap_billing(" \
                    "bill_item, " \
                    "bill_qty, " \
                    "bill_doc_date, " \
                    "bill_doc, " \
                    "bill_net_value, " \
                    "sales_order, " \
                    "import_date" \
                    ") VALUES (" \
                    "\"{}\", \"{}\", \"{}\", \"{}\"," \
                    "\"{}\", \"{}\", \"{}\"" \
                    ") ON DUPLICATE KEY UPDATE " \
                    "bill_qty = VALUES(bill_qty), " \
                    "bill_doc_date = VALUES(bill_doc_date), " \
                    "bill_net_value = VALUES(bill_net_value), " \
                    "import_date = VALUES(import_date) " \
                    "".format(
                        bill_item,
                        bill_qty,
                        bill_doct_date,
                        bill_doc,
                        bill_net_value,
                        sales_order,
                        import_date
                        )
            query = query.replace('\"None\"', 'NULL')
            query = query.replace('(None', '(NULL')
            query = query.replace('\"NaT\"', 'NULL')
            query = query.replace('(NaT', '(NULL')

            try:
                q1 = gesdb_connection.execute(query)
            except Exception as e:
                print(bill_item, bill_doc, sales_order, e)



    if __name__ == "__main__":
        engine_str = 'mysql+mysqlconnector://root:abc123@localhost/mydb'

        file_name = "tmp/dataload/so_tracking.XLSX"
        df = pd.read_excel(file_name)
        if df.shape[1] == 35 and compare_columns(list(df.columns.values)) == 1:
            insert_billing(df)
        else:
            print("Incorrect column count, column order or column headers.\n")

然而，当我通读excel然后打印它时，该列被读为float64。

import pandas as pd
df = pd.DataFrame({'Sales Order': [1217252835, 1217988754, 1219068439], 
                   'Billing Doc.': [3222102723, 3209781889, 3214305818]})
    >>> df
   Billing Doc.  Sales Order
0    3222102723   1217252835
1    3209781889   1217988754
2    3214305818   1219068439

Answer 1

我自己找到了解决方案，在此发布以记录它。

df = pd.read_excel(file_name, converters={'Billing Doc.' : str})
print(df['Billing Doc.'])

695    3251631331
696    3252012614
697           NaN
698    3252272451
699    3252359504
700    3252473894
701           NaN
702           NaN
703           NaN
704    3252652940
705           NaN
706           NaN
707           NaN
708           NaN
Name: Billing Doc., dtype: object

Answer 2

类似的事情发生在我身上，因为新列的索引与原始数据帧的索引不匹配，从而导致NaN，导致自动广播浮动。因此，请检查：

原始数据框的索引与新列匹配
新列包含NaN。

Answer 3

试试这个：

df = df.astype(str)

请注意，这非常无效

或在将每个值插入查询

之前将其转换为int

pandas自动将我的字符串列转换为float

3 个答案: