pandas 抑制数据框列中的科学格式
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Suppress Scientific Format in a Dataframe Column
提问by iprof0214
I have a column called accountnumber with values similar to 4.11889000e+11 in a pandas dataframe. I want to suppress the scientific notation and convert the values to 4118890000. I have tried the following method and did not work.
我有一个名为 accountnumber 的列，其值类似于 pandas 数据框中的 4.11889000e+11 。我想抑制科学记数法并将值转换为4118890000。我尝试了以下方法，但没有奏效。
df = pd.read_csv(data.csv)
pd.options.display.float_format = '{:,.3f}'.format
Please recommend.
请推荐。
采纳答案by floydn
I assume the exponential notation for the account numbers must come from the data file. If I create a small csv with the full account numbers, pandas will interpret them as integers.
我假设帐号的指数符号必须来自数据文件。如果我创建一个带有完整帐号的小 csv，pandas 会将它们解释为整数。
acct_num
0 4118890000
1 9876543210
df['acct_num'].dtype
Out[51]: dtype('int64')
However, if the account numbers in the csv are represented in exponential notation then pandas will read them as floats.
但是，如果 csv 中的帐号以指数表示法表示，那么 Pandas 会将它们读取为浮点数。
acct_num
0 4.118890e+11
1 9.876543e+11
df['acct_num'].dtype
Out[54]: dtype('float64')
You have 2 options. First, correct the process that creates the csv so the account numbers are written out correctly. The second is to change the data type of the acct_num column to integer.
您有 2 个选择。首先，更正创建 csv 的过程，以便正确写出帐号。二是将acct_num列的数据类型改为整数。
df['acct_num'] = df['acct_num'].astype('int64')
df
Out[66]:
acct_num
0 411889000000
1 987654321000
回答by user1319128
You don't need the thousand separators "," and the 3 decimals for the account numbers.
您不需要千位分隔符“,”和帐号的 3 位小数。
Use the following instead.
请改用以下内容。
pd.options.display.float_format = '{:.0f}'.format
