I am facing this problem while coding;
import pandas as pd
import matplotlib from matplotlib import dates as d
import datetime as dt
import matplotlib.pyplot as plt
import numpy as np
data = pd.read_excel(r'F:\Downloads\Book1.xlsx', index_col=0)
data.replace('NoData', np.nan, inplace= True)
data['Time'] = data.index.map(lambda x: x.strftime("%H:%M"))
Error:
AttributeError: 'str' object has no attribute 'strftime'
You can use the parse_dates argument in your read_excel() call, and this means pandas should convert the specified column to datetime objects:
import pandas as pd
import matplotlib from matplotlib import dates as d
import datetime as dt
import matplotlib.pyplot as plt
import numpy as np
data = pd.read_excel(r'F:\Downloads\Book1.xlsx', index_col=0, parse_dates=[0])
data.replace('NoData', np.nan, inplace= True)
data['Time'] = data.index.map(lambda x: x.strftime("%H:%M"))
The documentation for read_excel is here.
I think you can use the pd.to_datetime() function to get datetime as follows:
import pandas as pd
import matplotlib from matplotlib import dates as d
import datetime as dt
import matplotlib.pyplot as plt
import numpy as np
data = pd.read_excel(r'F:\Downloads\Book1.xlsx', index_col=0)
data.replace('NoData', np.nan, inplace= True)
data['Time'] = pd.to_datetime(data.index, format="%H:%M")
You can check the pandas documentation for further information here.
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
load_file=pd.read_excel(r'E:\CCNC\CCNCCodes\Modulated
output\plot_oriented_ss_data.xlsx',header=0)
load_file.columns
s=load_file.loc[0:49,['Timeseries','ccn_0.1']] s
s1=s
s['Timeseries'] = s['Timeseries'].astype(str)
plt.plot(s1[0:49]['Timeseries'],s1[0:5762]['ccn_0.1'],color='b')
plt.grid()
plt.show()
Please tell me where do I exact need to make the change to avoid the overlapping of time series in x-axis.
Instead of converting your 'Timeseries' to str, you should convert them to datetime using:
s['Timeseries'] = pd.to_datetime(s['Timeseries'])
How can I pick out just July-month of these time series? My time series goes from 1985-2018 with runoff values on the right side. I need to get some help with further code to pick out the July-values and then plot it.
my code:
from pandas import read_csv
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import os
import cartopy
from datetime import date,datetime
dir1 = "mystiations/"
files = os.listdir(dir1)
files = np.sort(files)
files_txt = [i for i in files if i.endswith('.txt_')]
df = pd.read_csv(dir1+files_txt[0],skiprows=6,header=None, index_col=0,sep=" ",na_values=-9999)
df.index = pd.to_datetime(df.index,format="%Y%m%d/%H%M")
parse_dates=True
index_col=0
myperiod = df["1985":"2018"]
myperiod
runoff
I am trying to develop a candlestick chart with matplotlib but for some reason, dates are not coming up in the x-axis. After searching in stackoverflow, I understood that the dates need to be converted to float numbers so i converted them as well but still it's not working. New to this python and matplotlib. ANy help would be greatly appreciated.
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.finance import candlestick2_ohlc
import matplotlib.dates as dts
import matplotlib.ticker as mTicker
from datetime import datetime
my_file=pd.read_csv("C:\\path\\to\\file\\file.csv",sep=",",names=['Date','Open','High','Low','Close','AdjClose','Volume'],skiprows=1)
dateseries=[]
for i in my_file['Date']:
dateseries.append(dts.date2num(datetime.strptime(i,'%Y-%m-%d')))
print(dateseries)
fig,ax1=plt.subplots()
candlestick2_ohlc(ax1,my_file['Open'], my_file['High'],my_file['Low'], my_file['Close'], width=0.7,colorup='#008000', colordown='#FF0000')
plt.show()
Sample data:
Date,Open,High,Low,Close,Volume1,Volume2
2017-05-08,149.029999,153.699997,149.029999,153.009995,153.009995,48752400
2017-05-09,153.869995,154.880005,153.449997,153.990005,153.990005,39130400
2017-05-10,153.630005,153.940002,152.110001,153.259995,153.259995,25805700
In general, you are right about "the dates need to be converted to float numbers". Then to display dates on x-axis, you would need to "convert" them back. If you don't mind using candlestick_ohlc, that might be easier for setting the x-axis for your case here:
import io
import matplotlib.pyplot as plt
from matplotlib.finance import candlestick_ohlc
from matplotlib.dates import date2num, DayLocator, DateFormatter
import pandas as pd
s = """Date,Open,High,Low,Close,Volume1,Volume2
2017-05-08,149.029999,153.699997,149.029999,153.009995,153.009995,48752400
2017-05-09,153.869995,154.880005,153.449997,153.990005,153.990005,39130400
2017-05-10,153.630005,153.940002,152.110001,153.259995,153.259995,25805700"""
my_file = pd.read_table(io.StringIO(s), sep=',', header=0)
my_file['Date'] = date2num(pd.to_datetime(my_file['Date']).tolist())
fig, ax=plt.subplots()
candlestick_ohlc(ax, my_file.as_matrix())
ax.xaxis.set_major_locator(DayLocator())
ax.xaxis.set_major_formatter(DateFormatter('%Y-%m-%d'))
plt.show()
import sys
import ConfigParser
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import datetime as DT
import bokeh
sys.path.extend(['..\..\myProj\SOURCE'])
fullfilepath = "../../myProj/SOURCE/" + 'myparts.txt'
ohg_df = pd.read_csv(fullfilepath, sep="\t" )
temp_df = temp_df[['as_on_date', 'ohg_qty']]
temp_df = temp_df.sort(['as_on_date'], ascending=[1])
temp_df.set_index('as_on_date')
plt.plot(temp_df.index, temp_df.ohg_qty)
plt.show()
This is my dataframe after importing.
I am trying to plot the line graph with x axis as date mentioned in the dataframe.
Can someone guide me... I am new to pandas.
dataframe picture
output pitcure
Easier:
# Set index directly
ohg_df = pd.read_csv(fullfilepath, sep="\t", index='as_on_date')
# Convert string index to dates
ohg_df.index = pd.to_datetime(ohg_df.index)
# Get a column and plot it (taking a column keeps the index)
plt.plot(ohg_df.ohg_qty)