I have the next DataFrame with string column ("Info"):
df = pd.DataFrame( {'Date': ["2014/02/02", "2014/02/03"], 'Info': ["Out of 78 shares traded during the session today, there were 54 increases, 9 without change and 15 decreases.", "Out of 76 shares traded during the session today, there were 60 increases, 4 without change and 12 decreases."]})
I need to extract the numbers from "Info" to new 4 columns in the same df.
The first row will have the values [78, 54, 9, 15]
I have trying with
df[["new1","new2","new3","new4"]]= df.Info.str.extract('(\d+(?:\.\d+)?)', expand=True).astype(int)
but I think that is more complicated.
regards,
Just so I understand, you're trying to avoid capturing decimal parts of numbers, right? (The (?:\.\d+)?
part.)
First off, you need to use pd.Series.str.extractall
if you want all the matches; extract
stops after the first.
Using your df
, try this code:
# Get a multiindexed dataframe using extractall
expanded = df.Info.str.extractall(r"(\d+(?:\.\d+)?)")
# Pivot the index labels
df_2 = expanded.unstack()
# Drop the multiindex
df_2.columns = df_2.columns.droplevel()
# Add the columns to the original dataframe (inplace or make a new df)
df_combined = pd.concat([df, df_2], axis=1)