我有这个txt文件:
Tu 11:44:00 119 52913161 DETECTOR STATE 0001
Tu 11:44:00 119 52913161 DETECTOR STATE 1100
Tu 11:44:02 119 52913161 DETECTOR STATE 0000
Tu 11:44:02 119 52913161 DETECTOR STATE 1110
Tu 11:44:04 119 52913161 DETECTOR STATE 0000
Tu 11:44:04 119 52913161 DETECTOR STATE 0011
我使用此代码在Python(Jupyter Notebook)中打开:
import pandas as pd
data= pd.read_csv('EXPORT20171205114501_1.txt', sep=" ", header=None)
data.columns = ["day", "time", "street", "sensor", "type", "state", "bits"]
我得到了这个输出:
day time street sensor type state bits
0 Tu 11:44:00 119 52913161 DETECTOR STATE 1
1 Tu 11:44:00 119 52913161 DETECTOR STATE 1100
2 Tu 11:44:02 119 52913161 DETECTOR STATE 0
3 Tu 11:44:02 119 52913161 DETECTOR STATE 1110
4 Tu 11:44:04 119 52913161 DETECTOR STATE 0
5 Tu 11:44:04 119 52913161 DETECTOR STATE 11
如何保持领先零?
我尝试过以下选项:
data = pd.read_csv('EXPORT20171205114501_1.txt', sep=" ", header=None, dtype={'column': object})
data = pd.read_csv('EXPORT20171205114501_1.txt', sep=" ", header=None).astype(str)
data = pd.read_csv('EXPORT20171205114501_1.txt', sep=" ", header=None, converters={'ColName': str})
以上选项均无效。我已经将熊猫更新到了最新版本。有什么想法吗?
答案 0 :(得分:3)
按列表使用列名称的参数名称,然后可以使用string
dtype
参数定义要解析为dictionary
的列:
names = ["day", "time", "street", "sensor", "type", "state", "bits"]
df = pd.read_csv('EXPORT20171205114501_1.txt', sep="\s+", names=names, dtype={'bits':str})
print (df)
day time street sensor type state bits
0 Tu 11:44:00 119 52913161 DETECTOR STATE 0001
1 Tu 11:44:00 119 52913161 DETECTOR STATE 1100
2 Tu 11:44:02 119 52913161 DETECTOR STATE 0000
3 Tu 11:44:02 119 52913161 DETECTOR STATE 1110
4 Tu 11:44:04 119 52913161 DETECTOR STATE 0000
5 Tu 11:44:04 119 52913161 DETECTOR STATE 0011
如果需要所有列作为字符串:
names = ["day", "time", "street", "sensor", "type", "state", "bits"]
df = pd.read_csv('EXPORT20171205114501_1.txt', sep="\s+", names=names, dtype=str)
print (df)
day time street sensor type state bits
0 Tu 11:44:00 119 52913161 DETECTOR STATE 0001
1 Tu 11:44:00 119 52913161 DETECTOR STATE 1100
2 Tu 11:44:02 119 52913161 DETECTOR STATE 0000
3 Tu 11:44:02 119 52913161 DETECTOR STATE 1110
4 Tu 11:44:04 119 52913161 DETECTOR STATE 0000
5 Tu 11:44:04 119 52913161 DETECTOR STATE 0011