pandas dataframe
>>> df2 = pd.DataFrame(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]),
... columns=['a', 'b', 'c'])
>>> df2
a b c
0 1 2 3
1 4 5 6
2 7 8 9pandas dataframe
>>> df2 = pd.DataFrame(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]),
... columns=['a', 'b', 'c'])
>>> df2
a b c
0 1 2 3
1 4 5 6
2 7 8 9panda python
# install pandas (basic, if path is not set yet)
py -m pip install pandas
# or set PATH to use pip:
setx PATH "%PATH%;C:<pathtopythondirectory>Scripts"
pip install pandas
# if "connection error: [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed" [!]:
py -m pip install --trusted-host pypi.python.org pip pandas
# if PermissionError: [WinError 5] Access is denied
py -m pip install --user pandas
# or via creating a virtual environment venv:
py -m venv c:pathtonewenvironment
# then execute:
c:pathtonewenvironmentScriptsactivate.batpandas
#for dropping a column in a dataframe
df = df.drop(['PassengerId'], axis = 1)
#for selecting all columns except one
df.iloc[:, df.columns != "Survived"]
#for checking nan values is a column
df['your column name'].isnull()pandas
df = pd.DataFrame(np.random.randn(1000, 4), index=ts.index,
.....: columns=['A', 'B', 'C', 'D'])
.....:
In [137]: df = df.cumsum()
In [138]: plt.figure()
Out[138]: <Figure size 640x480 with 0 Axes>
In [139]: df.plot()
Out[139]: <matplotlib.axes._subplots.AxesSubplot at 0x7f53723daa10>
In [140]: plt.legend(loc='best')
Out[140]: <matplotlib.legend.Legend at 0x7f5369d93dd0>Copyright © 2021 Codeinu
Forgot your account's password or having trouble logging into your Account? Don't worry, we'll help you to get back your account. Enter your email address and we'll send you a recovery link to reset your password. If you are experiencing problems resetting your password contact us
