Difference between revisions of "Panda: read csv datetime"
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Onnowpurbo (talk | contribs) |
Onnowpurbo (talk | contribs) |
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+ | ==Cara 1== | ||
+ | |||
+ | import pandas as pd | ||
+ | from datetime import datetime | ||
+ | headers = ['col1', 'col2', 'col3', 'col4'] | ||
+ | dtypes = [datetime, datetime, str, float] | ||
+ | pd.read_csv(file, sep='\t', header=None, names=headers, dtype=dtypes) | ||
+ | |||
+ | import pandas as pd | ||
+ | from datetime import datetime | ||
+ | headers = ['Time', 'Value'] | ||
+ | dtypes = [datetime, float] | ||
+ | pd.read_csv(file, sep=',', header=None, names=headers, dtype=dtypes) | ||
+ | |||
+ | |||
==Cara 1== | ==Cara 1== | ||
Line 11: | Line 26: | ||
==Cara 2== | ==Cara 2== | ||
+ | |||
+ | df = pd.read_csv(file, sep = ',', parse_dates= [col],encoding='utf-8-sig', usecols= ['Date', 'ids'],) | ||
+ | |||
+ | |||
+ | ==Cara 3== | ||
import numpy as np | import numpy as np |
Revision as of 10:01, 8 August 2019
Cara 1
import pandas as pd from datetime import datetime headers = ['col1', 'col2', 'col3', 'col4'] dtypes = [datetime, datetime, str, float] pd.read_csv(file, sep='\t', header=None, names=headers, dtype=dtypes)
import pandas as pd from datetime import datetime headers = ['Time', 'Value'] dtypes = [datetime, float] pd.read_csv(file, sep=',', header=None, names=headers, dtype=dtypes)
Cara 1
import pandas x = pandas.read_csv('/home/onno/TensorFlow/TEMP-train.csv', parse_dates=True, index_col='DateTime', names=['DateTime', 'X'], header=None, sep=',') print(x) x.info() print(x.head())
Cara 2
df = pd.read_csv(file, sep = ',', parse_dates= [col],encoding='utf-8-sig', usecols= ['Date', 'ids'],)
Cara 3
import numpy as np import matplotlib.pyplot as plt import pandas as pd infile = '/home/onno/TensorFlow/TEMP-train.csv' mydateparser = lambda x: pd.datetime.strptime(x, "%Y-%m-%d %H:%M:%S") df = pd.read_csv(infile, sep=',', names=['datetime', 'value'], parse_dates=['datetime'], date_parser=mydateparser)