[英]Write a pandas DataFrame mixing integers and floats in a csv file
I'm working with pandas DataFrames full of float numbers, but with integers in one every three lines (the whole line is made of integers).我正在使用充满浮点数的 Pandas DataFrames,但每三行一个整数(整行由整数组成)。 When I make a print df
, all the values displayed are shown as floats (the integers values have a ``.000000```added) for example :当我print df
,显示的所有值都显示为浮点数(整数值添加了“.000000”),例如:
aromatics charged polar unpolar
Ac_obs_counts 712.000000 1486.000000 2688.000000 2792.000000
Ac_obs_freqs 0.092732 0.193540 0.350091 0.363636
Ac_pvalues 0.524752 0.099010 0.356436 0.495050
Am_obs_counts 10.000000 59.000000 62.000000 50.000000
Am_obs_freqs 0.055249 0.325967 0.342541 0.276243
Am_pvalues 0.495050 0.980198 0.356436 0.009901
Ap_obs_counts 18.000000 34.000000 83.000000 78.000000
Ap_obs_freqs 0.084507 0.159624 0.389671 0.366197
Ap_pvalues 0.524752 0.039604 0.980198 0.663366
When I use df.iloc[range(0, len(df.index), 3)]
, I see integers displayed :当我使用df.iloc[range(0, len(df.index), 3)]
,我看到整数显示:
aromatics charged polar unpolar
Ac_obs_counts 712 1486 2688 2792
Am_obs_counts 10 59 62 50
Ap_obs_counts 18 34 83 78
Pa_obs_counts 47 81 125 144
Pf_obs_counts 31 58 99 109
Pg_obs_counts 27 106 102 108
Ph_obs_counts 7 49 42 36
Pp_obs_counts 15 83 45 65
Ps_obs_counts 57 125 170 216
Pu_obs_counts 14 62 102 84
When I use df.to_csv("mydf.csv", sep=",", encoding="utf-8")
, the integers are written as floats ;当我使用df.to_csv("mydf.csv", sep=",", encoding="utf-8")
,整数被写为浮点数; how can I force the writing as integers for these lines ?如何强制将这些行写入为整数? Would it be better to split the data in two DataFrames ?将数据拆分为两个 DataFrame 会更好吗?
Thanks in advance.提前致谢。
Simply call object
简单地调用object
df.astype('object')
Out[1517]:
aromatics charged polar unpolar
Ac_obs_counts 712 1486 2688 2792
Ac_obs_freqs 0.092732 0.19354 0.350091 0.363636
Ac_pvalues 0.524752 0.09901 0.356436 0.49505
Am_obs_counts 10 59 62 50
Am_obs_freqs 0.055249 0.325967 0.342541 0.276243
Am_pvalues 0.49505 0.980198 0.356436 0.009901
Ap_obs_counts 18 34 83 78
Ap_obs_freqs 0.084507 0.159624 0.389671 0.366197
Ap_pvalues 0.524752 0.039604 0.980198 0.663366
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