pandas - Read For Learn

Ignoring NaNs with str.containsv

There’s a flag for that: See the str.replace docs: na : default NaN, fill value for missing values. So you can do the following:

Normalize columns of pandas data frame

You can use the package sklearn and its associated preprocessing utilities to normalize the data. For more information look at the scikit-learn documentation on preprocessing data: scaling features to a range.

Get first row value of a given column

To select the ith row, use iloc: To select the ith value in the Btime column you could use: There is a difference between df_test[‘Btime’].iloc[0] (recommended) and df_test.iloc[0][‘Btime’]: DataFrames store data in column-based blocks (where each block has a single dtype). If you select by column first, a view can be returned (which is quicker than returning a copy) and the original dtype is preserved. In … Read more

Converting strings to floats in a DataFrame

NOTE: pd.convert_objects has now been deprecated. You should use pd.Series.astype(float) or pd.to_numeric as described in other answers. This is available in 0.11. Forces conversion (or set’s to nan) This will work even when astype will fail; its also series by series so it won’t convert say a complete string column